Financial activity with graphical user interface based on natural peril events

ABSTRACT

A financial activity network includes a central managing system connected to a plurality of participant terminals. Rules governing operation of the financial activity are stored for future reference. A participant provides investment information such as a map location for the predicted strike by the natural peril event and, optionally, one or more secondary parameters relating to the natural peril event, such as the time interval between the time of investment and the time of an event strike and/or the severity of the event strike according to an established scale. In one example, an external objective independent information source is consulted, with the external objective independent information source providing monitoring, interpretation and derived determination of parameters pertaining to the natural peril event. Methods and articles of manufacture are also disclosed.

CROSS-REFERENCE TO RELATED APPLICATION

This is a continuation-in-part of U.S. non-provisional patentapplication Ser. No. 11/312,662, filed Dec. 20, 2005 which claims thebenefit of U.S. Provisional Patent Application No. 60/637,784, filedDec. 21, 2004 and a continuation-in-part of U.S. non-provisional patentapplication Ser. No. 11/901,050, filed Sep. 14, 2007 which is acontinuation-in-part of U.S. non-provisional patent application Ser. No.11/312,783, filed Dec. 20, 2005 which claims the benefit of U.S.Provisional Patent Application No. 60/637,784, filed Dec. 21, 2004 whichare incorporated by reference herein in their entirety.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention pertains to financial activities and in particularto such activities in which a financial return may be paid out based ona participant's prediction of weather-related or other naturallyoccurring events, and especially such events monitored and documented byan independent external information source.

2. Description of the Related Art

Oftentimes, natural peril events contain sufficient energy to imposepotentially significant financial burdens arising from damage toproperty. It is the nature of such catastrophes that they cannot bepredicted with exact certainty, even in severity or number ofoccurrences within an event season or the exact time and/or duration ofan event. These types of natural peril events include, for example,earthquakes, tornadoes and tropical weather events such as cyclones, (aterm given to all circulating weather systems over tropical waters—andof special interest here, the Atlantic basin and eastern Pacific).Tropical cyclones include tropical weather events referred to as“hurricanes” if they are sufficiently strong. Tropical cyclones whichgrow in intensity so as to become hurricanes originate at sea and maymake landfall and travel along a land portion before dissipating orreturning to the sea. Homeowners and business insurance policiestypically contain deductible provisions ranging from 2% to 15% of thevalue of a home or worksite.

Further, these same policies do not provide any coverage for the outsideareas of a home or business such as landscaping, outside lighting,docks, fencing and the like. Often, property owners do not havesufficient flood insurance or have other omissions or insufficientcoverage which result in catastrophic financial losses in even thelowest rated hurricanes. Great losses suffered by property owners, suchas those located along coastal and outlying areas, can be overwhelmingfor those who cannot afford to be self-insured. Insurance companiesoffer substantial aid for these individuals, but economic strains causedby unusually active hurricane seasons have resulted in relatively highpremiums. In order to make certain that insurance protection isavailable to individuals on an ongoing basis, various legislation andregulations have been enacted. However, substantial economic burdensremain, such as high deductible amounts and excluded items, whichrepresent damage costs which must be borne directly by the individual.Further, there are considerable delays in obtaining insurance relief,due to a number of factors outside of the owner's control, such asdelays associated with adjuster scheduling, claim processing andgovernmental determinations. These delays are considerably extended whenwide scale damage occurs.

As if the present problems are not enough, it has been predicted thatthe increased storm activity of the past few years is likely to continuein the Atlantic basin for the next 15 to 20 years. One prediction for2006 is that 17 named storms will occur, nine of which can becomehurricanes and five of which are expected to develop into major storms,with winds of 111 mph or more. By comparison, in the year 2005, 26 namedstorms were reported. Of the 13 major storms that formed the past twoyears, seven struck the U.S., whereas, according to the historicalaverage, only one of every three reported storms would be considered“major” storms.

In addition to increased whether severity, other factors have been citedas causes for unexpectedly large damage estimates. For example, it hasbeen estimated that, by year 2020, a single Miami storm could causecatastrophic losses of 500 Billion—several times the damage inflicted byHurricane Katrina. This is attributed to the rise in additional propertydevelopment demanded by a growing population, along with a rise inpurchasing power with greater individual wealth. These estimates havenot included any consideration of inflation.

Other lessons are being learned from hurricane Katrina. For example, theGreat Miami hurricane of 1926 caused about $760 million in damage, in2004 dollars. Surprisingly, if the hurricane were to be repeated at thepresent time (the same magnitude and following the same track) damage isestimated to be as large as $130 billion, due in large part topopulation expansion in the area. In the year 2020, damage estimatesfrom the same hurricane are estimated to be as great as $500 billion. Inaddition to primary damage factors such as loss of property, otherfactors directly result from a natural event. For example, the FederalEmergency Management Agency (FEMA) has encountered significantdifficulty in providing temporary housing for disaster victims. Loss ofdwellings is aggravated by extensive loss of jobs, further slowingeconomic and personal recovery. For example, FEMA's hotel program for2005 cost the federal government $325 million and, at its peak, coveredapproximately 85,000 rooms.

Other natural activities are also forecasted to exhibit alarming trends.For example, a tsunami occurring in the next few years is anticipated toresult in a 60 Billion dollar disaster, imperiling 1 million residents,affecting 600,000 jobs locally and 2.5 million jobs nationwide. TheCalifornia State Seismic Safety Commission and others have urged thatlocal evacuation plans be upgraded to account for possible catastrophiclosses. For example, in one instance, losses are estimated to includethe closure of the ports of Los Angeles and Long Beach. A two-monthshutdown of the ports would cost $60 billion and affect 600,000 jobs inthe state and 2.5 million jobs nationwide.

SUMMARY OF THE INVENTION

The invention is generally directed to conducting financial activitiesbetween a provider and a plurality of participants, based on a naturalperil event such as a tropical cyclone, a tornado or an earthquake. Theparticipants are given an opportunity to predict the future occurrenceof the natural peril event, and to invest funds with the expectation ofa return on their investment if their prediction should match theoutcome of the natural peril event. The present invention is alsodirected to a less than catastrophic natural peril event that imperilsone's expectation of a skiing vacation or a week at what is hoped to bea sunny beach.

The invention in one implementation encompasses a system for conductinga financial activity based on a tropical weather event, including afinancial activity module for facilitating financial activity between aprovider and at least two participants utilizing a graphical userinterface, for receiving tropical weather event information from anexternal independent information source of such information and forproviding financial activity information to the participants utilizingthe graphical user interface, including information relating to thetropical weather event information and a plurality of geographic regionsin which the financial activity is to occur and in which a futuretropical weather event may occur, the regions presented as a mapdisplayed by the graphical user interface. At least one communicationmodule is provided for communication between the financial activitymodule and an external independent information source for receiving thetropical weather event information from at least one externalindependent information source, and for providing index informationutilizing the graphical user interface. The index information includesan index having an index value varying in response to one or moretropical weather events, and for presenting to the participants at leastone derivative product to be traded between the participants withrespect to a plurality of geographic regions. The derivative product hasa value that varies in response to the index value, and settled based onat least one of the tropical weather event information and the indexinformation.

In another implementation, the invention encompasses a system forconducting a financial activity based on a tropical weather event,utilizing a graphical user interface, including a financial activitymodule for facilitating financial activity between a provider and atleast two participants utilizing a graphical user interface, forreceiving tropical weather event information from an externalindependent information source of such information and for providingfinancial activity information to the participants utilizing thegraphical user interface, including information relating to the tropicalweather event information and a plurality of geographic regions in whichthe financial activity is to occur and in which a future tropicalweather event may occur, the regions presented as a map displayed by thegraphical user interface. The financial activity module provides atleast one derivative product to be traded between the participants, fora plurality of geographic regions, the derivative product having a valuethat varies in response to the index value, and settled based on atleast one of the tropical weather event information and the indexinformation. The financial activity module further provides indexinformation including an index having an index value varying in responseto one or more tropical weather events. At least one communicationmodule is provided for communication between the financial activitymodule and an external independent information source for receiving thetropical weather event information and for making available to theparticipants, the tropical weather event information and the indexinformation.

In another implementation, the invention encompasses a system forconducting a financial activity based on a natural peril event,utilizing a graphical user interface, including a financial activitymodule for facilitating financial activity between a provider and atleast two participants utilizing a graphical user interface, forreceiving natural peril event information from an external independentinformation source of such information and for providing financialactivity information to the participants utilizing the graphical userinterface, including information relating to the natural peril eventinformation and a plurality of geographic regions in which the financialactivity is to occur and in which a future natural peril event mayoccur, the regions displayed as a map displayed by the graphical userinterface. At least one communication module is provided forcommunication between the financial activity module and an externalindependent information source for receiving the natural peril eventinformation from at least one external independent information source.The financial activity module engages in providing index informationutilizing the graphical user interface, the index information includingan index having an index value varying in response to one or morenatural peril events and presenting to the participants at least onederivative product to be traded between the participants, for aplurality of geographic regions, the derivative product having a valuethat varies in response to the index and which is settled based on atleast one of the natural peril event information and the indexinformation.

In another implementation, the invention encompasses a method ofconducting a financial activity between a provider and a plurality ofparticipants, based on a tropical weather event, utilizing a graphicaluser interface, including the provider receiving ongoing tropicalweather event information from an external independent informationsource of such information. The provider provides financial activityinformation to the participants, utilizing the graphical user interface,including information relating to the tropical weather event informationand a plurality of geographic regions in which the financial activity isto occur and in which a future tropical weather event may occur, theregions presented as a map displayed by the graphical user interface.The provider engages in offering to the participants, using thegraphical user interface, first prediction data that changes over time,concerning a predicted outcome of the tropical weather event, receivingthe participants' prediction data of a predicted outcome of the tropicalweather event, using the graphical user interface, and receiving theoutcome of the tropical weather event from an external independentinformation source of such information. The provider or a third partycompares the participants' prediction data to the external informationto determine if the participant qualifies for successfully predictingthe outcome of the tropical weather event and, in one embodiment,engages in making the comparing determination available to theparticipants.

In another implementation, the invention encompasses a method ofconducting a financial activity between a provider and a plurality ofparticipants, based on a natural peril event, utilizing a graphical userinterface, including the provider receiving ongoing natural peril eventinformation from an external independent information source of suchinformation, and providing financial activity information to theparticipants, utilizing the graphical user interface, includinginformation relating to the natural peril event information and aplurality of geographic regions in which the financial activity is tooccur and in which a future natural peril event may occur, the regionspresented as a map displayed by the graphical user interface. Theprovider offers to the participants, using the graphical user interface,first prediction data that changes over time, concerning a predictedoutcome of the natural peril event, and receives the participants'prediction data of a predicted outcome of the natural peril event, usingthe graphical user interface. The provider also receives the outcome ofthe natural peril event from an external independent information sourceof such information. The provider or a third party engages in comparingthe participants' prediction data to the external information todetermine if the participant qualifies for successfully predicting theoutcome of the natural peril event, and, in one embodiment, making thecomparing determination available to the participants.

In one aspect, the present invention can be employed as a viablesolution to the economic and financial devastation which affectscitizens as well as governments caused by naturally occurringcatastrophes such as hurricanes. The present invention can be employedto offer an economic solution which does not use government or publicfunds and therefore does not require tax payer funding to replenishgovernment pools. In one aspect, the present invention can be employedto use only funds provided by private entities to augment governmentalfinancial assistance for catastrophic occurrences.

BRIEF DESCRIPTION OF THE DRAWINGS

Features of exemplary implementations of the invention will becomeapparent from the description, the claims, and the accompanying drawingsin which:

FIG. 1 is a schematic representation of a financial activity networkaccording to an embodiment of the present invention;

FIG. 2 is a schematic representation of a financial activity apparatusimplementing the present invention;

FIG. 3 is a schematic representation of a first participant terminal;

FIG. 4 is a schematic representation of a second participant terminal;

FIG. 5 is a schematic representation of a point-of-purchase participantterminal;

FIG. 6 is a schematic representation of a standalone participantterminal;

FIG. 7 is a schematic representation of a first data display;

FIGS. 8 a-8 f are schematic representations of a series of screendisplays; and

FIGS. 9-12 together comprise a schematic flow diagram representing oneexample of system operation.

FIGS. 13-18 are graphical depictions of data screens implementing afinancial activity;

FIG. 19 is a schematic drawing illustrating treatment given to a unitarea addressed in an exemplary financial activity;

FIG. 20 is a schematic representation of the relationship betweenfinancial investment unit prices and dates of participation in afinancial activity, prior to occurrence of a natural peril event;

FIG. 21 is a table showing examples of illustrative financial investmentunit prices;

FIG. 22 is a table showing Poisson probabilities and otherprobabilities;

FIG. 23 is a table illustrating trade-offs involved in choosing thenumber of financial activities to be run.

FIG. 24 is a schematic representation of a computer screen showing anintroduction to overview of the graphical user the subject invention;

FIG. 25 is a schematic representation of a computer screen showing anoverview of the graphical user interface of the subject invention,reflecting current conditions;

FIG. 26 is a schematic representation of a first computer screen showingthe graphical user interface of the subject invention directed to adetailed geographical location;

FIG. 27 is a schematic representation of a second computer screenshowing the graphical user interface of the subject invention directedto a detailed geographical location;

FIG. 28 is a schematic representation of a computer screen showing thegraphical user interface of the subject invention directed to anoverview of geographically related data for a given year;

FIG. 29 is a schematic representation of a computer screen showing thegraphical user interface of the subject invention offering menu choicesto a user, within the context of the chosen year;

FIG. 30 is a schematic representation of a computer screen showing thegraphical user interface of the subject invention offering menu choicesto a user, within the context of a given storm occurring in the chosenyear;

FIG. 31 is a schematic representation of a computer screen showing thegraphical user interface of the subject invention offering differentsets of data to a user, that are available within the context of a givenstorm, occurring in the chosen year;

FIG. 32 is a schematic representation of a computer screen showing thegraphical user interface of the subject invention identifying a firstchosen set of data selected by a user, for a particular day and time,that is available within the context of a given storm occurring in thechosen year;

FIG. 33 is a schematic representation of a computer screen showing thegraphical user interface of the subject invention identifying a dataevent selected by a user, for a first particular geographical positionfor a particular day and time, that is available within the context of agiven storm occurring in the chosen year;

FIG. 34 is a schematic representation of a computer screen showing thegraphical user interface of the subject invention identifying a dataevent selected by a user, for a second particular geographical positionfor a particular day and time, that is available within the context of agiven storm occurring in the chosen year;

FIG. 35 is a schematic representation of a computer screen showing thegraphical user interface of the subject invention displaying anothermenu choice chosen by a user, within the context of a given stormoccurring in the chosen year;

FIG. 36 is a schematic representation of a computer screen showing thegraphical user interface of the subject invention with sets ofprobability data available for selection by a user, for a particular dayand time, that is available within the context of a given stormoccurring in the chosen year;

FIG. 37 is a schematic representation of a computer screen showing thegraphical user interface of the subject invention with probability dataselected by a user, for a particular geographic location, day and time,that is available within the context of a given storm occurring in thechosen year;

FIG. 38 is a schematic representation of a computer screen showing thegraphical user interface of the subject invention identifying a forecastdata event selected by a user, for a particular geographical positionfor a particular day and time, that is available within the context of agiven storm occurring in the chosen year;

FIG. 39 is a schematic representation of a computer screen showing thegraphical user interface of the subject invention with probability datafor multiple natural peril events of a given year, along with relatedinvestment data;

FIG. 40 is a schematic representation of a computer screen showing thegraphical user interface of the subject invention displaying investmentdata for a particular geographical position for a particular day andtime;

FIG. 41 shows a display table of FIG. 40;

FIG. 42 shows a series of display tables;

FIG. 43 shows candidate pricing curve functions for an exemplary study;

FIG. 44 shows an exemplary time series of prices for an exemplary study;

FIGS. 45( a) and 45(b) show average payouts and price volatility for aparticular study;

FIG. 46 shows a table of data for a pari-mutuel pool; and

FIGS. 47 and 48 show a table of data for a pari-mutuel market.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

The invention disclosed herein is, of course, susceptible of embodimentin many different forms. Shown in the drawings and described hereinbelow in detail are preferred embodiments of the invention. It is to beunderstood, however, that the present disclosure is an exemplificationof the principles of the invention and does not limit the invention tothe illustrated embodiments.

For ease of description, financial activity networks and other systems,articles of manufacture, and apparatus embodying the present inventionare described herein below in their usual assembled position as shown inthe accompanying drawings and terms such as upper, lower, horizontal,longitudinal, etc., may be used herein with reference to this usualposition. However, the systems, articles of manufacture and apparatusmay be manufactured, transported, sold, or used in orientations otherthan that described and shown herein.

Introduction

On-line performances have been proposed for a variety of financialactivities. These activities may be divided in a number of differentways such as gambling and non-gambling activities, for example. Gamingor gambling systems are in place which emulates traditional gamblingactivities in an on-line, internet software-based program, giving theusers the look and feel of traditional gambling activities. Suchgambling variants have been extended to nontraditional games of chancebased on virtually any experience known to mankind. Although gamingactivities can receive substantial benefit from implementations of thepresent invention, the present invention can also be employed with gamesof skill and non-gaming financial transactions.

Financial activities may also take the form of sweepstakes offerings inwhich participants are eligible to participate in a drawing or otherselection of winners who share in or are otherwise are entitled to apool of money set aside for the purpose. In another example of financialactivities contemplated by the present invention, cell phone subscriberscan text message their vote, indication of approval or choice ofalternatives and be entered into a sweepstakes for their participation.

In one instance, the present invention is concerned with financialactivity based upon games of skill in which participants processhistoric and other data and apply scientific principles and acquiredanalytical skills to arrive at informed decisions relating to thepredictions of future naturally occurring activities. In one instance, aparticipant makes an investment based upon one or more informeddecisions, thereby contributing to a common pool from which payouts aremade, for example, based upon the accuracy, level of detail and timingof their prediction.

The present invention, in one instance, is also concerned withtraditional financial activities which lie outside the area of gambling.More specifically, in one example, the present invention is concernedwith allocating and managing a pool of money collected fromparticipants, i.e. market participants who seek to offset anunpredictable but nonetheless potentially catastrophic financial burdencaused by property loss due to natural peril events. In one instance,these types of financial activities are based upon the participant'sproperty interests. Although such financial investments do at times comewith a substantial element of risk in the expectation and amount ofreturn, it has long been recognized that such financial investments donot represent gambling activities.

The present invention finds immediate application in the field ofoffsetting losses of those who live or find themselves in a particulargeographic area subjected to natural peril events which causesignificant damage to their property interests (e.g. homes, businesses,rentals, and vacation shares). In one instance, the present invention isconcerned with offsetting losses without governmental interaction.Examples of such natural peril events supported by the present inventioninclude naturally occurring phenomena without human causality, such astropical weather systems such as hurricanes as well as other tropicalweather events.

The present invention is directed not only to catastrophic or disastertype weather or other natural events but also to “regular,”non-catastrophic or non-disaster weather or other natural events such asrain, snow, heat and cold usually regarded as severe or unwelcome, butnot catastrophic. For example, the present invention is directed tonatural events of virtually any type which are known to place financialor other burdens on people who suffer as a result of the event. in oneaspect, the financial activity contemplated herein need not be based onseverity of the natural event. Examples include business and/or personalloss (vacations, etc.) that could be hedged against the risk of naturalweather events such as (but not limited to) extreme days of rain, snow,heat, and cold. Excess cold and/or rain can disrupt the tourism andvacation industry. Unexpected snowfall can also disrupt travel and/oroutdoor events and lack of snowfall and high temperatures could disruptthe ski industry. Too many days of any weather extreme could affectbusinesses. This model provides way of hedging against any of theseevents should a minimum threshold be exceeded (example, more than 5 raindays during a specified number of period in a specific geographic areaduring a certain time of the year) or could even compensate individualsand/or businesses on an escalating scale (binary) based upon the numberof rain days exceeded in a given period for a given geographic area andtime of the year. Based upon the minimum conditional payout guarantees,one could lock in a minimum payment based upon a threshold being met.

The premise of the financial activity is that market participants canexercise personal initiative to research known naturally occurringactivity and make certain predictions relating to forthcoming activityfor a particular season or year. A return on their investment can bepaid out at year's end or once a natural peril event has concluded, withthe return being based upon certain factors such as the accuracy oftheir prediction, the amount of time between their investment and theoccurrence of a natural peril event, and the skillful use of establishedlaws of statistics and other resources available to a marketparticipant. Time and effort spent in researching natural activity canhelp to improve the accuracy of predictions made.

Any of the financial activities herein may be undertaken with one ormore participants, and the provider may comprise one or more separateentities.

External Objective Information Sources

In one instance, the financial activity incorporates conclusions,findings and reports of one or more external objective informationsources such as an independent disinterested third party that providespublicly available information and conclusions. The terms “external” and“independent” refer to entities which are separate from the providerand/or participants of the financial activity. In one instance, anexternal objective information source provides information pertaining toa natural peril event (in one example an indication that a definednatural peril event has occurred, and in another example, that thedefined natural peril event has concluded). In another instance, theexternal objective information source provides natural peril event data,such as a point of landfall or a land track of a storm originating atsea.

As discussed herein, the present invention is directed to financialactivities between a provider and one or more participants. Activitiesinvolving multiple participants are attractive in many instances, sincethe risk to a provider can be spread across a number of participants.However, the present invention also contemplates activity of virtuallyany type herein, conducted with a single participant who wishes tomitigate the risk of suffering setbacks due to a future natural event.The provider, must however, be willing to engage such an activity.

In one instance, the financial activities incorporate independentobjective information which is based upon naturally occurring eventsthat are studied by the external objective information source (andwhich, in one instance, is publicly available). In one example,financial activities contemplated by the present invention are directedto predictions of natural peril event activity, with financialinvestments being made before the activity has occurred and/orconcluded. Payouts or the assigning of points or other value accordingto a successful, matching outcome of the financial activity may be basedupon multiple factors, some of which are determinable by an externalobjective information source. Examples include the measurable severitywhich can be measured, for example, by the amount of property damage asdetermined by insurance institutes and government agencies. Payouts canalso depend upon metrics associated with the natural peril event, basedon details concerning occurrence of the natural peril event, such as itspoints or path of terrestrial contact and the timing of a participant'sinvestment such as the amount of lead time given by the marketparticipant prior to event conclusion.

In many instances, an external objective independent information sourceis relied upon for its expertise in studying, and measuring naturalperil event phenomena as well as drawing conclusions from data collectedfrom natural peril events. Oftentimes, reports made available to thepublic and others include inferences and conclusions drawn by an expertagency, which goes beyond a mere relating of observed facts. Informationwhich is key to carrying out a financial activity (such as the time andplace of occurrence of the natural activity) is obtained from a sourceexternal to the provider of the financial activity.

As will be seen herein, it is generally preferred that the identity ofthe external objective information source is defined beforehand, in arules database or in some other manner. In one instance, the externalobjective independent information source provides facts and conclusionswhich are made generally available to the public, or at least toindividuals likely to participate in the financial activity. In thismanner, individuals interested in participating in the financialactivity and those participants already engaged in the financialactivity can monitor progress of a natural peril event, independent ofthe financial activity. In one instance, participants in the financialactivity will be able to readily obtain expert information andskill-building technical intelligence from sources independent of thefinancial activity, thus enhancing motivation of the participants toengage in the financial activity with a greater likelihood of enjoying asuccessful outcome. Of particular interest here, are property ownersunable to obtain adequate insurance, but who nonetheless live in an areaknown to be subject to destructive natural peril events. Such propertyowners will have an interest in gaining an ability to predict naturalperil events, so as to be better able to protect their propertyinterests and to offset unforeseen damages. Others that might beinterested are cities and municipal corporations. Besides those thathave property interests at risk, interested parties may include thoseinterested in speculation types of financial activities, such asoperators of hedge funds and institutional type market participants.

Examples of external objective independent information sources includethe National Hurricane Center and the Tropical Prediction Center forhurricanes and other tropical storms.

Low-pressure tropical weather systems, or storms beginning at sea, startas relatively low energy thunderstorms. If a moving area ofthunderstorms in the tropics maintains its identity for 24 hours ormore, the weather system is termed a “tropical disturbance”. If theweather system exhibits a rotating or circulating weather pattern, theweather system is referred to as a tropical cyclone. The lowest energytropical cyclone is termed a “tropical depression” if its maximumsustained wind speed does not exceed 38 mph. For maximum sustained windspeeds ranging between 39 and 73 mph, the weather system is termed a“tropical storm”. The most intense weather systems are referred toeither as “hurricanes” or “typhoons”.

According to the National Hurricane Center, “hurricane” is a name for atropical cyclone that occurs in that oceanic area generally referred toas the Atlantic Basin or the eastern Pacific, and which is defined bymaximum sustained wind speeds of 74 mph or more. “Tropical cyclone” isthe generic term used for low-pressure systems exhibiting rotationalcharacteristics that develop in the tropics and meet a criterion forrelatively high maximum sustained wind speeds. The intensity ofhurricanes is measured according to the Saffir-Simpson scale (categories1 to 5).

It is well known that hurricanes and lesser storms develop from tropicaldepressions in the oceans where weather related factors cooperate toform and contribute energy to a low-pressure weather system. The weathersystem then travels across the ocean, along an unpredictable path. Ofinterest here are weather systems exhibiting circulating behavior whichgrow in intensity so as to develop into hurricanes which travel with agenerally westward direction component and make landfall or otherwisecontact property along well-defined geographical areas, such as theeastern coast of Canada, the United States, Mexico, and South America aswell as sea islands lying in a path of travel toward those land bodies.The class of storms referred to as “hurricanes” vary in intensity andare generally free to travel along their own unique pathway or “track”.Hurricanes are observed by independent expert agencies of the UnitedStates government, such as the National Hurricane Center (an example ofan external objective information source), which carefully records,analyzes and later publishes reports, findings and conclusions, whichare made available to the public.

Hurricanes are powered by the sea's thermal energy and by energy in theatmosphere. Generally speaking, hurricanes are directed by the easterlytrade winds. Around the center, core or “eye,” wind speeds accelerate togreat velocities. Moving ashore, these energetic winds displace theocean inwardly, toward land and are known to spawn tornadoes and producetorrential rains and floods. In the Atlantic Basin, for example,statistically there is an annual average of 8.6 tropical storms for theyears 1886-1998. Of these, 5.0, statistically, are hurricanes. The aboveillustrates aspects of natural peril events which may be employed in arules database or program or other structure to govern operation offinancial activity.

It is important to define early on those natural peril events which willqualify for consideration by the financial activity. For example,hurricanes considered by the financial activity may be limited to onlythose hurricanes which make terrestrial contact or which have a minimumstrength. In another example, it is important to define natural perilevents considered by the financial activity when the members of thepublic may have alternative definitions which vary from those to beconsidered by the financial activity. For example, participants whosuffered damage during the time of a tropical cyclone may not fallwithin the “best-track” or other report issued by an external,independent, objective information source (such as NHC/TPC) (informationemployed according to one of the possible rules of operation). Contraryto popular expectations, a particular participant may suffer damage fromnatural phenomena lying outside of the tropical event of interest to thefinancial activity.

Other examples of external objective independent information sourcesinclude the National Hurricane Center for hurricanes and other tropicalstorms, the National Weather Service and the Storm Prediction Center fortornadoes in the United States, and the Geological Survey, NationalEarthquake Information Center for earthquakes in the United States.Additional examples include third parties that provide indexes of damageor risk of damage for financial investors and insurance companies.

Examples of Natural Peril Events

Consideration will now be given to a few examples of independentlyobservable, moving or otherwise changing natural peril events, and inparticular, those events capable of causing substantial damage.

A tornado is a violently rotating column of air in contact with theground that extends from a particular type of cloud formation referredto as a “cumulonimbus cloud”. Tornadoes can be categorized as “weak”,“strong”, and “violent”; with weak tornadoes often having a thin,rope-like appearance, with rotating wind speeds no greater than about110 MPH. The typical “strong” tornado often has a recognizablefunnel-shaped cloud associated with a high energy whirling updraft androtating wind speeds ranging between 110 and 200 MPH. Tornado severityis also measured according to the Fujita scale.

Scientific tornado research is performed by the National Severe StormsLaboratory (NSSL) which has been a leader in Doppler radar development,research and testing, and which has run numerous field programs to studytornadoes and other severe weather. Tornado research is also conductedby NCAR (National Center for Atmospheric Research) located in Boulder,Colo., and TORRO located in the United Kingdom. Almost every universitywith an atmospheric science program, as well as many local NationalWeather Service (NWS) offices, have also published some tornado-relatedstudies. The National Weather Service is a branch of the United Statesgovernment organized under the US Dept of Commerce, and the NationalOceanic and Atmospheric Administration (NOAA). In the United States, theNational Weather Service (NWS) issues tornado forecasts nationwide.Warnings come from each local NWS office. The Storm Prediction Center,located in Norman, Okla. and organized under NOAA/National WeatherService, and the National Centers for Environmental Prediction, issuewatches and severe weather outlooks. Information concerning tornadoes inCanada is managed by the Meteorological Service of Canada.

Tropical cyclones are low-pressure weather systems that develop at sea,especially at low latitudes, usually beginning as relatively low-energytropical depressions. As storm energy builds, tropical depressions beginto exhibit a rotating or circular weather pattern, and if the stormintensity is sufficient it is classified as a tropical cyclone. Tropicalcyclones include “tropical storms,” but the most intense tropicalcyclones are referred to (depending on the ocean basin in which theyoccur) as “hurricanes,” “typhoons,” or simply “cyclones.” According tothe National Hurricane Center, “hurricane” is a name for a tropicalcyclone that occurs in that oceanic area generally referred to as theAtlantic Basin, and which is defined by certain minimum wind speeds.“Tropical cyclone” is the generic term used for low-pressure systems ofgreat intensity that develop in the tropics and meet a criterion forrelatively high minimum sustained wind speeds. The intensity ofhurricanes is measured according to the Saffir-Simpson scale.

It is well known that hurricanes and less energetic tropical weatherevents develop from tropical depressions in the oceans, where weatherrelated factors cooperate to form and contribute energy to alow-pressure weather system. The weather system then travels across theocean, along an unpredictable path. Of interest here are weather systemsexhibiting circulating behavior which grow in intensity so as to developinto hurricanes which travel with a generally westward directioncomponent and make landfall or otherwise contact property alongwell-defined geographical areas, such as the eastern coast of Canada,the United States, Mexico, South America and sea islands lying in a pathof travel toward those land bodies. The class of storms referred to ashurricanes vary in intensity and are generally free to travel alongtheir own unique pathway or “track”. Hurricanes are observed byindependent expert agencies of the United States government, such as theNational Hurricane Center (an example of an external objectiveinformation source), which records, analyzes and later publishesreports, findings and conclusions, which are made available to thepublic.

An earthquake is a shaking of the ground caused by the sudden breakingand shifting of large sections of the earth's rocky outer shell. Theearth is divided into three main layers—a hard outer crust, a softmiddle layer and a center core. The outer crust is broken into massive,irregular pieces called “plates.” An earthquake is associated with asudden motion or trembling in the Earth caused by the abrupt release ofstrain slowly accumulated in the Earth's plates. It is reasonable toexpect that future earthquakes in known earthquake areas will havemagnitudes generally comparable to the magnitudes of past earthquakes.Seismologists use a magnitude scale, such as the Richter scale, toexpress the seismic energy released by an earthquake.

Typical effects of earthquakes vary from a Richter magnitude less than3.5 (generally not felt, but nonetheless recorded) to a Richtermagnitude 8 or greater (so-called “great earthquakes” which can causeserious damage over large areas measured in hundreds of kilometers).Although earthquakes can have similar magnitudes, their effects can varygreatly according to distance, ground conditions, and man-madeconstruction techniques. Publicly available, independent third-partystudies are reported by the U.S. Geological Survey. For example, the USgeological survey reports Earthquake Density Maps of the United States,as well as Shake Maps and Seismogram Displays for recent earthquakeactivity in United States and throughout the world. The U.S. GeologicalSurvey, National Earthquake Information Center, World Data Center forSeismology in Denver, issues detailed reports of significant earthquakeactivity for local areas of the United States and maintains anearthquake catalog useful for earthquake predictions.

The above illustrates aspects of exemplary natural peril events whichmay be employed in a rules database, program, derivatives contract orother structure to govern operation of financial activity. It isimportant to define early on those natural peril events which willqualify for consideration by the financial activity. For example,tornadoes considered by the financial activity may be limited to onlythose tornadoes which make terrestrial contact or which have a minimumstrength. In another example, it is important to define natural perilevents considered by the financial activity when the members of thepublic may have alternative definitions which vary from those to beconsidered by the financial activity. For example, participants whosuffered damage during the time of a tropical cyclone may not fallwithin the “best-track” issued by an external, independent, objectiveinformation source (such as NHC/TPC) set up by the financial activity asthe conclusive source of such information. That is, contrary to popularexpectations, a particular participant may suffer damage from naturalphenomena which are not encompassed by the financial activity.

As mentioned, the present invention contemplates natural peril eventsthat are not related to hurricanes. Such natural peril events may bedescribed as natural peril events originating either on land (such astornadoes, hail storms, wildfires or earthquakes), at water level (suchas tsunamis and rogue waves caused by winds in contact with the watersurface) or below water level (such as tsunamis caused by underwaterearthquakes).

Examples of Financial Activity Models

Different types of financial activities are carried out, typicallybetween a financial activity provider and one or more participants inthe financial activity. The activity may also be conducted betweenpaired or matched trading partners, as where bids are matched withpurchases. The pools of money supporting the financial activity can bemanaged on a pari-mutuel basis or not. For example, a financial activitycan be conducted to provide a fixed payout to one or more eligibleparties. Pricing can be structured in a number of different ways, suchas where prices are determined by market conditions, or by one or morealgorithms, or a mixture of these and other possibilities. Differentmodels of financial activities are contemplated, including:

1. Derivative trading type of financial activity, such as thoseactivities directed to derivative securities interests, which aretypically monitored by the Securities and Exchange Commission or otheroversight bodies, such as the Commodity Futures Trading Commission (anindependent agency of the United States government), the New York StockExchange, the Chicago Mercantile Exchange, the Iowa Electronic Market,and others. Examples include futures contracts, options contracts andoptions on future contracts. Trading may be unilateral or multilateraland may be cleared, either initially or later on, by an exchange.

2. Secondary trading of financial assets developed by a participant ofone or more of the financial activities indicated herein, particularlysecondary trading between a participant of an ongoing financial activityand a third party wishing to deal directly with the participant, ratherthan the financial activity provider. The financial activity providermay require registration of the secondary trade or impose other controlsover the parties involved, including assistance with executing the tradebetween two or more participants or nonparticipants, such asregistration of the instruments traded.

3. Persons with cell phones or other portable communication devices suchas pda's or laptop computers, may vote their choice of first landfalland are charged for placing the vote. Voting may be carried out via textmessaging, the internet or voice communication, with or without the useof voice recognition technology. Those participating may, for example,be entered into a sweepstakes that may or may not include a secondsweepstakes for those who vote in favor of a particular choice.

4. Price-oriented competition, preferably in games of skill whereparticipants are charged an “entry fee” to engage in skillfulcompetition with other participants. The distribution or “prize” toqualifying participants is predetermined at the outset of competition,and accordingly is not affected by variability factors. However, ifdesired, the “entry fee” can be adjusted by variability factors such asthose relating to the time interval between investment and eventoutcome, and the probability of a successful outcome determinedapproximately at the time of investment.

5. Property value protection, particularly financial activities in whichthe participants are screened for eligibility to engage in the financialactivity, depending upon some indication of their property rights in ageographical area covered by the financial activity.

6. Games of skill, preferably where the participants are obliged todemonstrate a level of skill which pertains to the natural peril eventsof interest.

7. Lotteries, sweepstakes or other games of chance, such as thoseactivities monitored by state and local governments.

Financial Activity Network

Referring now to the drawings, and initially to FIGS. 1-4, financialactivity system 100 in one instance, takes the form of a financialactivity network generally indicated at 10. In one example, network 10includes a central managing system 12 linked to a plurality ofparticipant terminals 14-18. The terminals can comprise, for examplevirtually any device that provides communication with a workstation suchas a network or other computers including desktop, portable, lap-top ormainframe computers, data terminals, dumb terminals, personal digitalassistants, cellular phones or other electronic devices havingcommunications capabilities. Throughout the description given herein,“computer” refers to a computer system comprising one or more computingdevices, but could also refer to computer systems operated by stockmarkets, options exchanges, commodity exchanges or the like.

As schematically indicated in FIG. 1, each of the participant terminalscommunicate directly with central managing system 12 via communicationnetwork components 15, allowing concurrent transactions and datatransfers to occur. Other types of arrangements are possible. Forexample, communications between the central managing system and theparticipant terminals can employ virtually any communications technologyknown today. The geographical spacing between the central managingsystem and the participant terminals can have virtually any scaledesired. For example, the entire network 10 can be located in a singleroom, or in a single building or building complex or campus.

As will be seen herein, financial activity can take place according todifferent models. One model is directed to a derivative tradings type offinancial activity, such as those activities directed to derivativesecurities interests. In this type of financial activity, the centralmanaging system 12 preferably comprises a brokerage system communicatingwith an exchange system. Preferably, participants' trading is conductedthrough the brokerage system before being conducted with the exchange.If desired, in this type of financial activity, the brokerage system canbe omitted with participants dealing directly with the exchange system.If desired, the central managing system can either be incorporated into,or be provided in addition to, the exchange system.

Alternatively, the financial activity network 10 can be located atvarious nationwide or international locations, as may be desired. As afurther alternative, the financial activity network may take on anyform, and may employ wire, cable or wireless components (such as cellphones, text messaging devices, pda's, etc), for example. Network 10 canbe configured as an open connection or network such as the Internetnetwork, a wide area network, a telephone network, a satellite network,an on-line network or a closed circuit television network or the likeintra-facility network. Network 10 can also take the form of an Ethernetarrangement, a token ring, a token bus or any other suitablecommunications arrangement or configuration that can link workstations,particularly workstations including one or more data processingcomputers.

Financial activity can, but need not necessarily, take place eitherwithin or across local, state, federal, national or internationalboundaries. For example, participant terminals can be located in one ormore boundaries, e.g., political boundaries different from that of thecentral managing system. As a further example, although the centralmanagement system and the participant terminals are located within agiven boundary, e.g., a given political boundary, the central managementsystem may communicate with external objective, independent informationsources, external credit agencies or other agencies located within oneor more different political or geographic boundaries. As will be seen,operators of the financial activity may rely entirely on outsideservices to provide the needed credit and other financial arrangements.

The terminals can comprise one of the many different types of electronicdevices known today, including a programmable computer, a telephone, astand-alone machine such as an ATM machine, a television or a set-topbox unit, a credit card reader, a kiosk terminal, a point-of-purchaseregister, or a stand-alone unit resembling an arcade game, for example.The terminals preferably include an input device suitable for receivinga purchase request or other data from a participant, such as thoseemployed by purchasers to obtain goods and/or services from a merchant.The input devices can take many forms, including a keypad (includingthose used in cellular and other portable devices), keyboard touchscreen or mouse or a remote control device, contactless payment system,or fingerprint or other biometric system, for example. Systems, articlesand apparatus preferably comprise digital devices, but could alsocomprise analog or hybrid electronic or non-electronic devices, as maybe desired.

System Apparatus

Turning to FIG. 2, financial activity system 100 includes systemapparatus 13 embodying the central managing system 12 shown in FIG. 1.In one example, system apparatus 13 comprises one or more storagedevices 20, one or more processors 22, and one or more interfacecomponents 24. The processor 22 in one example comprises a centralprocessor unit (“CPU”). The processor 22 executes one or moreinstructions of one or more programs 30, under control of an operatingsystem 35 employing one or more system programs 37. The program 30 inone example comprises one or more subroutines and one or more variables,as will be understood by those skilled in the art. The storage device 20in one example comprises at least one instance of a recordable datastorage medium, as described herein. The storage device 20 stores theprogram 30, and one or more databases 32, and one or more data files 34.

The interface component 24 in one instance comprises a graphical userinterface (“GUI”). In one example, the interface component 24 allows aservice provider or other user 38 to execute one or more programs 30.The program 30, in one example, comprises one or more subroutines, tocarry out the financial activity methods and operations to be describedherein. In one instance, program 30 includes one or more subroutines tocollect, publish, interpret or otherwise process information whichsupports principles and other aspects of operation of the financialactivity. In another instance, program 30 includes one or moresubroutines for implementing rules of operation for the financialactivity.

In another example, the interface component 24 allows the user 38 toverify or otherwise interact with one or more results of the program 30.In yet another example, the interface component 24 allows the user 38 toset one or more input values or operating parameters for the program 30.In the preferred embodiment illustrated in FIG. 2, interface component24 includes a display device 42 and a data input device 44 which allow auser 38 to set up the central managing system according to desiredoperating objectives. With the interface component 24, a user canaccess, read or write to the program 30, the databases 32 and the datafiles 34

Included in the apparatus 13 embodying system 12 is a communication port50 which provides two-way communication with the terminals 14-18.Communication port 50 can employ virtually any communications protocol,data format and other organizational, communication or other knowncontent that is in use today. It is generally preferred that thecommunications network employed between the central managing system andthe participant terminals comprise an interactive device taking anysuitable form.

The financial activity system 100, in one example, comprises a pluralityof components such as one or more of electronic components, hardwarecomponents, and computer software components. A number of suchcomponents can be combined or divided in the financial activity system100. An exemplary component of the financial activity system 100 employsand/or comprises a set and/or events of computer instructions written inor implemented with any of a number of programming languages, as will beappreciated by those skilled in the art. The financial activity system100 in one example comprises any (e.g., horizontal, oblique, orvertical) orientation, with the description and figures hereinillustrating one exemplary orientation of the financial activity system100, for explanatory purposes.

The financial activity system 100 in one example employs one or moremachine (e.g. computer)-readable (hereinafter “computer-readable”)signal-bearing media. The computer-readable signal-bearing media storesoftware, firmware and/or assembly language for performing one or moreportions of one or more embodiments of the invention. Examples of acomputer-readable signal-bearing medium for the financial activitysystem 100 comprise a storage component such as the one or more storagedevices 20. The computer-readable signal-bearing medium for thefinancial activity system 100 in one example can comprise one or more ofa magnetic, electrical, optical, biological, and atomic data storagemedium. For example, the computer-readable signal-bearing medium cancomprise floppy disks, memory devices, magnetic tapes, CD-ROMs,DVD-ROMs, hard disk drives, and electronic memory. In another example,the computer-readable signal-bearing medium comprises a modulatedcarrier signal transmitted over a network comprising or coupled with thefinancial activity system 100, for instance, one or more of a telephonenetwork, a local area network (“LAN”), a wide area network (“WAN”), theInternet, and a wireless network.

Data Structures

In a general sense, data needed for a financial activity may be locatedentirely on site, as contemplated herein. Alternatively, the presentinvention also contemplates situations where administrators of afinancial activity may decide to divide responsibilities with an outsideservice. For example, a credit or other financial service may be engagedto provide credit checks, authorize financially responsible individualsto participate, or even handle all financial matters, including thecollection, payout and other handling of funds. As another alternativecontemplated by the present invention, financial activities may beconducted with authorized brokers, financial institutions as well asregulated exchanges such as stock and futures exchanges. Such activitiesmay reflect predefined financial arrangements. In any of these orpossibly, other instances, the data handling, participant authorizationand other interactions concerning the participant may reside off-site,that is, remote from the operation (and possibly the responsibility) ofthe financial activity.

With reference to FIGS. 2-4, the databases 32 in one example comprise aparticipant database, an administrator or system database, a creditprovider's database, a storm watch database, a rules database and a pushdatabase. The credit provider database contains a list of creditproviders and their accepted methods of payment, as well as any creditrelated information of any type, such as authorization codes usuallyprovided to merchants or the like to authorize transactions acceptableto a credit provider. The credit provider database may also containother financial information associated with the credit provider, such asthe credit provider's identification number and account information. Inthe preferred embodiment, the system administrator in one aspectprovides services similar to that of a merchant selling goods and/orservices to participants. If desired, the system administrator cancomprise a reseller of goods and services such as proprietary weatherreports and cartographic or weather information, as well as maps, formsand other materials relating thereto. In another example, operators ofthe financial activity may rely entirely on outside services to providethe needed credit and other financial arrangements.

The participant database maintains a list of participants and theirassociated personal financial information. The participant databasestores a set of personal payment methods which are registered by theparticipant with a transaction processing service, which in thepreferred embodiment is engaged by the system administrator as anaccommodation to the participant. The participant database furtherincludes information regarding the eligibility of participants toparticipate in the financial activity. In the preferred embodiment, thesystem administrator employs a known screening service to enforce thoserules set down pertaining to restrictions on participation. For example,the system administrator may choose to implement requests by governmentofficials to curtail or otherwise limit transactions originating in orcommunicated to those areas subject to an evacuation order or one ormore legal restrictions. Further details concerning an exemplaryscreening service is provided in U.S. Pat. No. 6,508,710, issued Jan.21, 2003, the disclosure of which is hereby incorporated by reference inits entirety.

For example, a participant could specify by checking a box on a list asto whether he is registering as an individual, corporation, partnership,trust, etc. Depending upon which box is checked, another display willask what the entity's net worth is. Should that net worth meet or exceeda set amount for that particular entity, then the participant will beregistered for that activity based upon a minimum net worth set by thefinancial activity provider or regulated exchanges (i.e.—eligiblecontract participant, institutional trader, retail trader, etc.).

The storm watch database tracks storm activity of interest toparticipants. Included, for example, are circulating storm systems whichhave not yet matured into hurricanes, but which have the potential fordoing so. If desired, historical data concerning previous storm systemsmay be made available to participants, either on an unrestricted basisor at additional cost to the participant.

The administrator database contains data and other information needed tooperate the financial activity. Included, for example, are ongoing“real-time” or “moving” totals of the number of participants, the totalinvested, the number of other participants that have positions (e.g.financial investment units) corresponding to a participant's predictionchoice, and the amount invested by the other participants. If desired,the administrator database can also include real-time estimates ofpayout amounts corresponding to the participant's prediction choice,assuming that the choice proves to be accurate. Such payouts may includeconsideration of some form of minimum return the participant may expect,for those financial activities providing such expectations. Theadministrator database can also include a list of known users who are tobe barred from participating or otherwise restricted in theirparticipation activity. This information can be contained in a separatedatabase, if desired. Also, the administrator database preferablycontains participation statistics and financial statistics, useful inproviding an updated estimate of the cost of doing business foroperating the financial activity. If desired, adjustments to coverfluctuations in overhead costs can be made with regard to futureparticipants.

The rules database contains rules or other principles of operation forthe financial activity. The rules database contains a set of “rules” orprinciples which govern the ongoing financial activity, in a specific orin a general way (e.g. rules defining the authorities, or externalobjective independent information sources to be relied upon for a final,factual decision or conclusion). Examples of such authorities includeexpert governmental agencies responsible for monitoring natural perilevents, as well as weather stations which provide reports. The rulesalso include eligibility requirements, personal financial paymentrequirements, and sliding scales affecting payouts such as timing anddeadlines.

The rules may be wholly or partially public (i.e. available toparticipants) or private (i.e. available only to those authorized by thesystem administrator). In one instance, the rules database also governsthe course of conduct of specific aspects of the financial activity. Forexample, in one instance, the rules include definitions relating to thenatural peril events to be considered by the financial activity, theexternal objective independent information source which managesinformation and determinations concerning a natural peril event whichwill be relied upon during the course of conducting the financialactivity, parameters associated with the natural peril events,especially those parameters which are used to uniquely define eachparticular natural peril event as well as parameters for determiningremuneration points or other value.

If desired, the points or other value pertaining to the participant'sremuneration can be “hidden” or incorporated within a calculation, andneed not be expressed in an explicit reference. In another instance, therules database contains definitions of those participants eligible toengage in the financial activity, as well as those participants whichqualify as finalists (“winners”) eligible or who otherwise qualify forremuneration. In a further instance, the rules database containsprinciples of operation governing transfers between the financialactivity and qualifying participants. The rules database may also governaccess that a participant has to certain information concerning thefinancial activity, such as the number of individuals participating, theaverage or largest financial investments currently being made, and theraw total currently collected for the event of interest.

In another instance, the rules database can include principles ofoperation relating to safety and public interest considerations. Forexample, the rules database can provide for automatic suspension ofoperation upon public announcement of an evacuation order orrecommendations to prepare to evacuate a particular area. The rulesdatabase can provide for selective activity based upon the location ofthe participants. For example, suspension of financial activity can belimited only to those counties or other areas where government safetywarnings have been issued, while allowing financial activity to continuefor those areas not affected by the government warnings.

The push database contains information useful for generating interestand encouraging participant activity. For example, push data can includerecent designations of officially recognized storm systems that maybecome candidates for future investment opportunities. Push data canalso include brief analyses and/or statistics of ongoing or recentnatural peril events. Different amounts of push data and different listsof push participants can be set up by a computer program according topre-defined “trigger levels” such as storm location, intensity andspeed, for example. The push database can also include rules ofoperation pertaining to push data, such as local times during which pushdata is or is not sent.

The data files comprise data information which, preferably, isrelatively static, such as the official designations of natural perilevents to be issued in an upcoming activity season, official andunofficial historical reporting of natural peril events activity andstatistics compiled from historical information, for example. Thishistorical data can be combined with climatological and otherprobabilities to determine investment price and/or payouts. If desired,the data files can be replaced by one of the available databases, or aspecial database can be provided, if desired.

A land area database can contain geographic items such as maps and otherdata relevant to conducting a financial activity. For example, in theUnited States, maps can be provided for those states at risk to ahurricane strike. Preferably, the maps would be “clickable” to allow aparticipant to readily indicate the state of interest. In response, moredetailed maps such as maps of the counties within the state would bedisplayed to the participant and again, would be clickable to provideready indication of the participant's choices of predicted strike areas.If desired, this same functionality can be provided in table form orsome other form convenient for user participation. In addition, a crossreference “finder” tool can be provided to receive Zip code informationor the like, and return with a colored or other visually distinctivearea on the displayed map, or a textual response to the inquiry, readyfor the participants' selection to the indicated. As mentioned, it isgenerally preferred that the maps, tables, or other geographic locationinformation contain a visual indication of those areas which lie outsideof the financial activity, providing a ready indication of ineligibilityto participants surveying their possible choices for a prediction entry.If desired, the geographic location data can be linked to meteorologicalor climatological data for the given area.

A weather database is preferably provided for information concerningweather, meteorological or climatological or other natural forces suchas precursors to earthquakes or volcanic eruptions. The weather databasepreferably contains historical information helpful to those preparing aprediction of future natural peril events.

Participant Terminals

Turning now to FIG. 3, terminal apparatus 58 comprises one or more ofthe participant terminals 14-18 and includes a communications port 60,one or more processors preferably comprising a central processing unit62 and a memory storage unit 64. Also included is an interface component68 which preferably comprises a display 70 and a data input device 72.Interface component 68 allows a participant or other user 76 tocommunicate with apparatus 58 and in turn with apparatus 13 of thecentral managing system 12. The present invention also recognizes othertypes of devices, such as pda's laptop computers and cellularcommunication devices, as means for conducting financial activitiesaccording to the present invention. As will be seen herein the presentinvention also contemplates an organization of equipment and servicesthat may be loosely be referred to as a network in which third partyservices such as clearing houses or exchanges participate in thefinancial activity, along with the aforementioned participants and theoriginators or managers of the financial activity.

Turning now to FIG. 4, terminal apparatus 80, comprising another exampleof the participant terminals, includes a communication port 60, one ormore processors preferably comprising a central processing unit 62, amemory storage unit 64 and an interface component 84. In the arrangementillustrated in FIG. 4, interface component 84 includes, in addition to adisplay 86 and a data input device 88, a card read/write device 92 andan output device 94 for dispensing a printed receipt, confirming aparticipant's transaction.

With additional reference to FIGS. 5-6, two additional examples ofparticipant terminals are shown. With reference to FIG. 5, participantterminal 200 is shown comprising a display 202 for presentinginformation about the selected natural peril events, a user interfaceintegrated with the display for viewing event information and placinginvestments on a selected natural peril event, an optional cardread/write device 206 for receiving an electronic or magnetic-stripecard encoded with a participant's account information, an optionalticket dispensing device 210 for providing a ticket comprising purchaseinformation for a selected natural peril event and a housing 214 forretaining the display, the user interface, the card read/write deviceand the ticket dispensing device.

The participant terminal 200 also includes a processor and may alsoinclude a speaker (not shown) for playing audio associated with thefinancial activity information. The display preferably comprises a CRTor a flat screen display 218 for displaying information regarding thenatural peril events and preferably, the display comprises atouch-sensitive display, including a touch-sensitive membrane (notshown) in communication with the processor for selecting the desiredinvestment information such as the desired investment in terms ofdollars or the number of financial investment units, as well as“scrolling” between next and previous information. As will be apparentto those skilled in the art, any appropriate type of display may beused.

Turning now to FIG. 6, another embodiment of the at least oneparticipant terminal, generally indicated at 230, is shown comprising adisplay 232 for presenting information about the selected natural perilevent, a user interface 236 for viewing event information and makinginvestments, an optional card read/write device 240 for receiving anelectronic or magnetic-stripe card encoded with a user's accountinformation, an optional ticket dispensing device 242 for providing aticket comprising investment information for a selected natural perilevent and a stand-up type housing 250 for retaining the display, theuser interface, the card read/write device and the ticket dispensingdevice. The participant terminal also includes a processor (not shown)for facilitating financial activity. The participant terminal 230 mayalso include a speaker (not shown) for playing audio associated with thefinancial activity information. The examples shown in FIGS. 5 and 6 areonly exemplary implementations for the at least one participantterminal, and other configurations are also contemplated. For example,the user interface may include a plurality of hardware or softwarebuttons, each identifying different functions for facilitating variousaspects of the financial activity.

Central Managing Apparatus

The central managing apparatus 13 and the participant terminal apparatus(together, referred to as “the apparatus”) in one example comprise aplurality of components such as one or more of electronic components,hardware components, and computer software components. A number of suchcomponents can be combined or divided in the apparatus. An exemplarycomponent of the apparatus employs and/or comprises a set and/or seriesof computer instructions written in or implemented with any of a numberof programming languages, as will be appreciated by those skilled in theart. The apparatus in one example comprises any (e.g., horizontal,oblique, or vertical) orientation, with the description and figuresherein illustrating one exemplary orientation of the apparatus, forexplanatory purposes.

The apparatus, in one example, employs one or more computer-readablesignal-bearing media. The computer-readable signal-bearing media storesoftware, firmware and/or assembly language for performing one or moreportions of one or more embodiments of the invention. Examples of acomputer-readable signal-bearing medium for the apparatus comprise thestorage components 20, 64. The computer-readable signal-bearing mediumfor the apparatus in one example comprises one or more of a magnetic,electrical, optical, biological, and atomic data storage medium. Forexample, the computer-readable signal-bearing medium may comprise floppydisks, magnetic tapes, CD-ROMs, DVD-ROMs, hard disk drives, andelectronic memory. In another example, the computer-readablesignal-bearing medium may comprise a modulated carrier signaltransmitted over a network comprising or coupled with the apparatus, forinstance, one or more of a telephone network, a local area network(“LAN”), a wide area network (“WAN”), the Internet, or a wirelessnetwork.

The present invention also contemplates arrangements where some or allof the central managing services are performed by one or more thirdparties, such as clearing houses as well as professional third partyservices authorized to conduct financial or management functions.

Graphical User Interface

Turning now to FIGS. 7 and 8 a-8 f, and initially to FIG. 7, program 30includes one or more subroutines for communicating with a participantlocated at a remote participant terminal. In one instance, program 30includes one or more subroutines for generating one or more screensperforming a number of functions, including sending information to aparticipant, and receiving information from the participant. In FIG. 7,window or screen 300 schematically represents a summary screen forparticipant John Doe, as indicated at 310. As mentioned, screen 300 is asummary screen, and works with a number of supporting screens whichquery the participant for specific information such as the participant'sname, and receives responsive information which is then reviewed forform and content, recorded in one or more databases such as theparticipant database, and is reported in the area 310.

Other supporting screens receive other participant applicationinformation, such as the participant's location of residence or locationof other property holdings, along with information regarding theparticipant's credit information, or approval from an external service,such as a participating brokerage service. Upon approval, eitherinternally or through an exchange clearing organization or the likeservice, the participant's credit and other qualifications, an accountis opened for the participant and details concerning the account, creditqualifications and other related financial information are stored in oneor more databases, such as the participant database. Alternatively,operators of the financial activity may rely entirely on outsideservices to provide the needed credit and other financial arrangements.The steps referred to herein regarding credit check and the like may bereplaced by an authorization from the external service. In otherinstances, operators of the financial activity may interact directlywith an approved exchange service, with financial arrangements beingmade according to rules governing operation of the exchange.

In any event, the summary screen 300 is then presented to theparticipant, confirming the participant's active status in the financialactivity. During this process, one or more queries, multiple-datachoices, multiple activity choices or other interactions with theparticipant are listed in the area 314. If desired, each choicepresented to the participant can have an adjoining checkbox 318,provided for the ready data input into program 30. If desired, one ormore command buttons 320-330 can be provided for the user, to executeone or more commands or otherwise control some portion of data is storedin one or more databases, or to control some portion of program 30allocated to the participant by the system administrator. If desired,area 334 can be provided to display context-sensitive rules of play tothe participant, or to provide appropriate prompts or other helpfulinformation. If desired, checkboxes 336 can be provided adjacent eachentry in window or pane 334 to allow the participant to obtain furtherinformation related to the topic of interest.

In the area 340, the participant is alerted to the current operationbeing performed by program 30. If desired, a sequence of operationsappearing in area 340, along with appropriate responsive indicationsfrom the participant may be listed in area 344. If desired, informationin area 344 can be saved or printed using command buttons 328, 330, thusaffording the participant the opportunity to obtain a written record ofthe activities in either electronic or printed paper form.

Turning now to FIGS. 8 a-8 f, a events of exemplary data input screensare shown in schematic form. These screens pertain generally to theselection of the locations chosen by the participant for investment. Forexample, if the natural peril event is a hurricane, the location may bethe participant's prediction of where a hurricane strike will maketerrestrial contact. Alternatively, the location may be the epicenter ofthe storm's strike, the point of landfall, or a point along the overland track of the tropical cyclone. Landfall can be defined in anynumber of ways. For example, landfall can be measured using the centerof the eye of hurricane, or the eye wall of the hurricane or differentportions of the structure of the hurricane. Referring to FIG. 8 a, ascreen 400 presents a map 402 of a land area, which is preferablysubdivided into smaller portions, each of which may either be selectableby the participant or shaded or otherwise made visually distinctive tothe participant so as to indicate an area which is not eligible for thefinancial activity.

If desired, the rules stored in one or more databases may providefurther information regarding this topic of ongoing activity.Preferably, each subdivided portion of map 402 is selectable by touchscreen, click and point, or by an input pen device, for example. It isalso preferable, in one instance, that the area 406 selected by theparticipant is shaded, colored, or otherwise made visually distinctiveso as to indicate graphically the choice made by the participant. InFIG. 8 a, area 406 is chosen by the participant and receives adistinctive contrasting color value to provide visual feedback to theparticipant. As indicated in FIG. 8 a, the screen 400 also includes aquery to the participant to confirm and finalize the choice of location.

Turning now to FIG. 8 b, screen 410 is presented as a prompt to theparticipant to expand the indicated area so as to include one or moresurrounding areas. In screen 410, an enlarged area 412 surrounding theinitial chosen location 406 (the “collar countries”) is made to flash orblink on and off or undergo a color change. An optional text message ispresented to draw the participant's attention to the advantages ofenlarging the selected location in which a natural peril event strike ispredicted to occur. The participant can indicate additional locations byshift-clicking, for example.

In one instance, it may be desirable to establish a rule of playallowing the use of so-called secondary parameters. These secondaryparameters require a participant to select not only a location of strikeby a natural peril event, but also to indicate some characterizingfactor associated with the natural peril event, such as binary eventsincluding the strength of the tropical storm measured according to anumerical category value, according to the Saffir-Simpson scale, forexample. Another example of a secondary parameter for a tropical stormcould be the strength of the storm, and such is contemplated in FIGS. 8c-8 f. Referring to FIG. 8 c, screen 420 provides notice to theparticipant that a secondary parameter is to be provided, in addition tothe strike location. In FIG. 8 d, a pull-down window 424 is provided inscreen 426 to indicate a range of values to be chosen by the participantas the predicted category strength of the hurricane strike. In FIG. 8 e,it is assumed that a participant has previously enlarged the area ofstrike location to be covered by the chosen investment or “stake”. Inscreen 430, the participant's choice of category 2 is confirmed alongwith an invitation to spread the participant's stake in categorystrength, as well as in land area. In FIG. 8 f, a screen 440 shows theparticipant's selected range of category strength. Following, is ascreen (not shown) which summarizes the participant's stake. Forexample, for the investment indicated in FIG. 8 f, a user has selectednine geographic areas and three category strengths, for a total purchasecost of 27 financial investment units (9 areas×3 strength values). Inone instance, it is generally preferred that this summary total offinancial investment units purchased is reported in area 344 of screen300, shown in FIG. 7.

Methods and Operations

An illustrative description of exemplary operation of the system isconsidered with initial reference to FIGS. 9-12. As will be seen, thefinancial activity discussed here is modeled after a game of skill orthe like. Other types of financial activities will require differentmethods, apparatus and operations.

FIGS. 9-12 indicate a series of steps to be carried out during thecourse of the financial activity. These method steps may be implementedin a number of different ways, including, for example, but notlimitation, execution of program 30 by the central managing apparatus13, and one or more participant terminals. The program 30 may beimplemented by either a general-purpose computer or a special purposeelectronic device, for example. The method steps may be incorporatedinto an article of manufacture such as a data storage device. As will beseen herein, the steps indicated in FIGS. 9-12 indicate that portion offinancial activity as taken from the viewpoint of the systemadministrator.

Referring initially to step 500, the financial activity is initiated byvirtually any appropriate means. For example, if the rules of operationprovide that the financial activity begins at a given date and time, thestart step 500 may be implemented in software that monitors the systemclock and executes program code which publishes invitations toparticipants to engage in financial activity as of the referenced dateand time. Alternatively, start step 500 may be initiated by the systemadministrator pressing a key switch or otherwise activating a switch toinitiate transmission to participants indicating that the financialactivity season has been opened. An event season may be related to asingle natural peril event or a number of different natural peril eventsor a number of portions of an ongoing natural peril event. In oneinstance, an event season is defined by calendar dates, by a number ofoccurrences of a defined natural peril event, or by a mixture of both,or may rely upon a report or other dissemination of data from anexternal objective independent information source.

In step 502 in addition to announcing the opening of the financialactivity season, an optional offer is made to make available certainrules of operation which govern financial activity for the season ofoperation. In step 504 application information is obtained from theparticipants. This information can include, for example, an indicationof the identity of the participant, the participant's residentiallocation or location of property interests, and the participant's creditinformation needed to allow the system administrator to authorizeopening of an account for the participant. Alternatively, theadministrator may rely upon external credit or other financial servicesto take the necessary action culminating in authorization of aparticipant's account. Preferably, the system administrator predefinesacceptance criteria in the rules which govern the financial activity.These rules may include intervention by an external agency, such as anexternal credit agency from which credit is purchased by theparticipant, using the system administrator as a broker, as is currentlydone by many merchants offering goods or services for sale.

In step 506, the application information is reviewed and the decisionmade in step 508 is to either accept or reject the participant'sapplication. For example, a participant's application may be rejectedbecause the participant has failed to disclose a property interestneeded to base financial activity on property losses caused byoccurrence of natural peril events. If the participant's application isrejected, control is passed to step 511 which sends a terminationmessage to the participant and returns control to step 504.

If the participant's application is accepted, control is passed to step510 in which credit information is obtained from the participant. Theparticipant's credit qualifications are reviewed in step 512 and adecision is rendered in step 514 to accept or reject the participantbased upon the added requirements of appropriate credit qualifications.Again, if the participant fails to meet sufficient creditqualifications, control is passed to step 511 which sends a terminationmessage to the participant and then transfers control to step 504. Ifthe decision in step 514 is positive, indicating acceptance of theparticipant's application and credit qualifications, control is passedto step 516 which confirms the active status of the participants withrespect to the financial activity. Such confirmation may be indicated,for example, by a report rendered by screen 300 as explained above, withreference to FIG. 7.

Referring to FIG. 10, in step 518 the prediction entry is requested fromthe participant. In the step, the participant provides informationdefining the investment to be made. After confirming the unique identityof the natural peril event, the participant declares the primaryparameter information which, in one instance, comprises the location ofthe land strike predicted for the natural peril event. Thereafter, theparticipant declares any secondary parameters required by the rules ofoperation, such as the severity of the strike, and the strike duration,for example. In step 520, the prediction entry and other investmentinformation is obtained from the participant and stored in one or moredatabases, for future reference. In one instance, the time at which theinvestment information is obtained is noted and stored along with theparticipant's investment data. In one instance, the amounts of payout orremuneration to a successful participant is weighted according to theamount of time between the investment transaction and occurrence of theevent, with greater time durations being weighted more favorably, on thepremise that later investments have the benefit of accumulated knowledgewhich will benefit the ability to predict occurrence of an event.

The investment information is reviewed in step 522 and judgment is madein step 524 as to whether the investment information is acceptable ornot. If the investment information is rejected in step 524, control ispassed to step 526 which sends an error message to the participant,passing control to step 518 to repeat the information gathering process.If desired, step 526 can cause relevant information to be offered ordisplayed to the participant to help raise the participant's level ofskill in making a prediction. If desired, the participant can be askedto answer a number of questions relating to the skills involved inmaking a prediction for the particular natural peril event.

Assuming that the investment information is in the correct form andmeets other automated criteria, control is passed to step 528 in whichthe investment information is recorded along with the current time. Asmentioned, this information, and resulting decisions to authorize aparticipant may be as simple as receiving a favorable indication from anexternal credit entity, clearing house, or the like service. The systemadministrator has the option of determining at what point in the ongoingfinancial activity a participant is deemed to have completed theinvestment process for the purpose of determining the time differencebetween the investment and occurrence of the natural peril event. Forexample, the times noted in either steps 520 or 528 (or some other timeif desired) can be used. As a further alternative, a systemadministrator may wish to defer appointing an investment time to theparticipant until monies for the transaction have been obtained from theparticipant. As a concession to the participant, the systemadministrator may provisionally appoint an investment time at an earlierstep.

Assuming the investment information has been successfully obtained andrecorded, control is passed to step 530 in which necessary monies arecollected from the participant. If desired, the participant's ability topay can be guaranteed before hand to eliminate any time delay at thispoint in the ongoing financial activity. Further, as mentioned above,these and other financial arrangements may be handled by an externalagent or service, or may be otherwise provided for according to variousregulatory bodies. In step 532, the participant's investment isconfirmed by an entry to the summary screen 300, for example. Withreference to FIG. 11, control is then passed to step 534 in whichcontact is made with an external objective independent informationsource that observes the natural peril event and manages informationconcerning the natural peril event and optionally, renders relateddecisions, such as assigning a severity level according to establishedscales of measure.

Generally speaking, it is preferred that the system administrator not berequired to render decisions concerning occurrence of a natural perilevent, such as primary and secondary event parameters. In one instance,a system administrator provides in the rules of operation that afinancial activity will rely upon a designated external objectiveindependent information source for information concerning the occurrenceand characteristics and other parameters of natural peril events uponwhich investments are to be based. In step 534, connection to anexternal objective independent information source may be initiated oralternatively, data from the external objective independent informationsource previously obtained may be accessed for use by the financialactivity. In step 536 updates to ongoing developments received from theexternal objective independent information source may be posted for thebenefit of existing and prospective participants. In one instance,updates are made on an ongoing “live” basis, either with little or notime delay, or at a minimum, at a time prior to closing of a naturalperil event.

In step 538, information from the external objective independentinformation source is queried to determine if the external objectiveindependent information source has established start of a natural perilevent of interest to the financial activity. If an event has not yetstarted, control is passed to step 536. When the external objectiveindependent information source determines that an event has started, aunique identifier for the natural peril event is assigned and recordedto one more databases. In one instance, the unique identifier isthereafter associated with each investment by a participant concerningthe natural peril event. In step 540, the start of the event is reportedto the participants and the time of event starting as “officially”determined under rules of the system administrator is posted orotherwise made available to participants, and is recorded in one or moredatabases for possible future reference by the financial activity. Instep 544, if the event has not yet closed, continuous updates regardingevent progress are obtained and in one instance, are reported orotherwise made available to the participants.

Once an event has closed, control is passed to step 546 to determine iffinancial activity has ceased. In one example, the system administratorprovides the rules of operation defining the starting and ending timesfor a financial activity season. This can be based upon an arbitrarydate and time, or upon occurrence of a particular event, such asoccurrence of the fourth, fifth, or sixth tropical cyclone since theseason opened. In one instance, closing of one season may be followed byan immediate or delayed opening of a subsequent season. For example, asubsequent season can be declared by the system administrator toaccommodate financial investments based upon occurrence of the fourth,fifth or sixth tropical cyclone occurring in a given hurricane season,as defined by the National Hurricane Center.

Referring to FIGS. 11 and 12, if it is determined in step 546 that aseason has ended, the season of financial activity is closed in step 548and accumulated data and other information is reviewed in step 550 todetermine and identify the finalists which have made successfulpredictions concerning the natural peril event, as provided in the rulesof operation for the financial activity. In step 552 a number ofcalculations are made in preparation for making payouts to thesuccessful finalists. In one instance, calculations are made todetermine the total holdings, the remuneration points per finalist, theadministration and operating fees associated with conducting thefinancial activity, and the amounts of remuneration for each finalist.Remuneration points, in one instance, are based solely upon the primaryparameter, which is preferably the strike location of the natural perilevent. In another instance, remuneration points are determined not onlyby the strike location but by other natural peril event parameters,secondary or otherwise.

If desired, an additional outcome, called a “null” event may be definedfor a financial activity. The null event is an investment choice made toparticipants, giving them the opportunity to invest in the possibleoutcome where there is no U.S. hurricane landfall in the currentoperating period, such as any number of different weather events,seasons or years. Participants investing in the null outcome, forexample, may receive a return at the end of hurricane season or otheroperating period.

In one instance, a single primary parameter is defined by the systemadministrator in the system rules of operation. In another instance, oneor more secondary parameters are also defined in the system rules ofoperation. In a further instance, secondary parameters are assigned alesser weighting than the primary parameter. In any event, the primaryand secondary parameters, if any, can have equal or unequal weighting,as may be desired. In one example, relating to hurricane events,location of the hurricane's strike is defined as a primary parameter,with time delay between the investment time and the time of thehurricane strike at the investment location being defined as a secondaryparameter.

In one instance, the time delay secondary parameter is weighted lessthan the primary parameter. In another instance, severity of the naturalperil event at the predicted location declared by a participant isdefined as a tertiary parameter, and the secondary and tertiaryparameters are assigned unequal weighting. Remuneration points may bedetermined according to a mathematical formula, algorithm, market pricesor other operation which does not require human intervention at the timeof execution. Thus, the formula, algorithm or other operation may beincorporated in an analog or digital electronic circuit or a hydrauliccircuit, for example. If desired, and especially with financial activityproviding a hedge against property losses, remuneration points may bedetermined, contingent upon or otherwise based upon confirmation of theparticipant's property interests.

In step 554 payouts are made to the successful participants, orfinalists. In step 556 the financial activity is closed.

The steps or operations described herein are just exemplary. There maybe many variations to these steps or operations without departing fromthe spirit of the invention. For instance, the steps may be performed ina differing order, or steps may be added, deleted, or modified.

In addition to the above, other types of activities are contemplated. Asmentioned above, a participant may elect to contact a systemadministrator or other service provider to engage in a financialactivity. Investments are paid into a system account to purchasefinancial investment units in the financial activity. Assuming aparticipant's activities are successful and perhaps if certainqualifications are met, payouts are made from the system account to theparticipant. Other types of transactions include, for example, financialinvestment units purchased in the course of the financial activity caneither be uniquely assigned to a participating individual, or they canbe made freely transferable. Accordingly, a financial activity may beorganized such that either payouts must be made to the participantmaking the investment or payouts can be made to any individualpossessing sufficient identification, such as an account number andpassword.

In either example, the investment positions are referred to herein asfinancial investment units or stakes, whether in the nature of aderivative holding or not, can be bought and sold between variousparties, either with or without interaction with personnel associatedwith the financial activity. If desired, the aftermarket activity infinancial investment units transfer can be offered by the operator ofthe financial activity as a service to members of the public. In anyevent, the financial activity, from investment to pay out would becarried out by operators of the financial activity. In anotherembodiment, financial activities can also be carried out between two ormore participants, with the operator of the financial activity providinga service that facilitates financial interactions between the partiesinvolved. Alternatively, the administrators of the financial activitymay elect to engage a brokerage institution, exchange, or clearingorganization, for example, to handle financial and related functions.

Variability Factors

Different factors affecting price and/or payout or settlement of thefinancial activity can be employed as an alternative to, or incombination with, market pricing that depends on market activity of thefinancial operation. By way of introduction, two considerations arecontemplated in one instance, one relating to probability (e.g. one ormore probabilities) and the other relating to a calendar or timing ofevents. In one instance, a price or cost variation in the purchase of afinancial investment unit (or “stake”) representing a quantification ofa participant's financial involvement is provided. Other variabilityfactors include numerical expressions, either continuous ordiscontinuous, of the impact, predicted impact or risk of an impact ordegree of impact of a natural peril event.

In one instance, assuming a point in time before occurrence of a naturalperil event, participants are able to invest in a financial activity atprices which are set by the financial activity provider, and which varydepending on time and/or on one or more probability factors. A firstcomponent of price variability, in one instance, keeps track of thetiming of the investment. It should be borne in mind that investmentscan be made a long time (e.g. months) before a natural peril event, suchas the time a hurricane would be likely to occur. One purpose of thisvariability factor (namely that of timing), is to encourage investmentsto be made earlier, rather than later. This variability factor, ineffect, preferably operates as a price discount factor, although thevariability factor could also be applied to payout distributions.

One or more probability assessments are preferably made at the time of aparticipant making an investment in the financial activity. Oneprobability assessment preferably takes the form of a probabilitycalculation based on current conditions, of the likelihood of a “hit,”“successful outcome” or “qualification” that a participant's predictionwill occur. For situations involving hurricane natural peril events, theprice of a unit available for purchase by a participant at a given timeis calculated based upon a probability that the county (or othergeographical designation for a purchase unit) chosen by the participantwill suffer a hurricane strike. If desired, probabilities can be basedupon storms other than hurricanes and if desired the strength of thestorm or other factor can be employed to alter the purchase price at anygiven time.

Related to probability-type variability factors are scales or indexesupon which a financial activity may be based, in whole or in part, incombination with other types of variability factors and other treatmentsconsidered herein. Scales can be employed to provide a basis forpricing, payout or other settlement of a financial activity. As will bediscussed in greater detail below, scales can be based upon observednatural activity, as well as characterizations, measurements and otherquantifications thereof. Thus, the scales may be used to introduce acertain measure of variability into the financial activity, which can becombined, if desired, with algorithms or other devices, as discussedherein. Scales, play a role in financial activities involving derivativesecurities interests, as where indexes are traded bilaterally ormultilaterally, as discussed herein. Scales are usually termed “indexes”in this context.

As a further consideration, financial activities can take into accountone or more conditional probabilities. The following example employsthree stages of probabilities, with reference to one example of anatural peril event dealing with hurricane activity. It has beenobserved that the average number of hurricane landfalls on the U.S. in agiven year is 1.7. This value is sufficient to define a Poissondistribution, according to conventional techniques, for numbers of U.S.landfalls, which yields a probability of 0.817 that at least one USlandfalling hurricane will occur in a given year. Similarly, from thisPoisson distribution, the conditional probability that there will be atleast two US landfalling hurricanes, given that one has alreadyoccurred, is 0.620.

In one instance, financial investment units in later portions of thefinancial activity (held, for example, for subsequent natural perilevents) can be priced more cheaply than earlier events according toconditional probabilities of K strikes, given that K−1 strikes havealready occurred, so that, in addition, prices go up in subsequentevents when an earlier event closes.

As mentioned, the financial activity, cited as an example of variabilityfactors, incorporates three stages of probability assessment, withdifferent probability treatments being given at each stage. Preferably,three probability treatments are applied to investment price, but couldalso be applied to payout distributions if desired. In a first stage ofprobability assessment, no storms or other precursors to hurricanes arein existence, and the first stage probabilities preferably are based onclimatological relative frequencies.

Second stage probabilities are in play where at least one storm or othernatural peril event exists in the field of interest (usually, ageographic area such as the Atlantic basin) but is far enough away fromthe area of interest (e.g., the coastline of the continental UnitedStates and adjacent coastlines) that no forecasts of imminent impact ofthe natural peril event, such as landfall, can be made. Preferably, forhurricane natural peril events, attention is paid at this stage totropical depressions, and tropical cyclones such as hurricanes and totheir location and tracks at sea. Preferably, in addition to thedistance between the tropical depression and the area of interest,attention is paid to the historical tracks or paths of storms inprevious years that subsequently made landfall in the area of interest.

In the third stage, occurrence of a natural peril event such as theimminent impact of the natural peril event (e.g. landfall of ahurricane) is officially recognized and preferably quantified as to itsimmanency. It is generally preferred that the existence of the thirdstage is declared, based upon an indication of an independent objectiveinformation source, such as the National Hurricane Center/TropicalPrediction Center. For example, a provider of a financial activity maylook to the issuance of hurricane watches, and especially hurricanewarnings from the National Hurricane Center (NHC) where a hurricanewatch is issued when it is determined that hurricane conditions maythreaten an area within 24 to 36 hours. At this point, preparations maybe made for an imminent evacuation, if one is ordered. A hurricanewarning is issued when hurricane conditions (i.e. maximum sustained windspeeds of 74 mph or more) are expected in a specified coastal areawithin 24 hours or less. Local government agencies make independentassessments and independently issue evacuation orders for people in theaffected areas. Notification of these types of events to the financialactivity provider can be used to close further participant activity, oralternatively to trigger a shift from stage two probability assessmentsto stage three probability assessments. The NHC forecasts go out 72 or120 hours into the future, depending on the nature of the forecastproduct. It should be noted that in this scenario, the effect of stagethree probability assessments is intentionally weakened by the calendaror the timing variability factor. Since the natural peril event isimminent, price discounts for unit purchases is preferably very low ornil. If desired, payout penalties can be assessed for stage threeinvestments because of their close timing to occurrence of the naturalperil event.

Considerations Regarding Pricing

In general, the pricing paid by participants of the financial activityis in one instance, based on the concept that the participants are giventhe option of investing more or less, as they may desire. It ispreferred that this be implemented by offering the participants theability to purchase investment positions in discrete quantities,generally referred to herein as “financial investment units.” In someinstances, depending on the financial activity, these financialinvestment units may be identified as shares or options. However, thepresent invention also contemplates financial activities where theamount of investment available to each participant is fixed, with theprice for the fixed amount being either constant or changing throughoutthe financial activity.

In general, pricing may be held at a fixed level, or may vary throughoutone or more portions, as well as the entirety of the financial activity.For example, operators of the financial activity may choose to varyprice according to variability factors, such as those described herein(e.g. according to an algorithm or according to the timing of theinvestment). As a further alternative, pricing may vary in whole or inpart according to market conditions, with pricing reacting to marketactivity. In such instances, the pricing may vary directly, inproportion to, or in some amount, but in the same general trend as,changes in market activity. Further, market activity can becharacterized in a variety of ways, such as direct relation to the totalnumber of units in play or in some proportional or nonproportionalmanner based on some aspect of market activity. Pricing and/or marketactivity may take into account “current” and “recent” market changes.

Examples of pricing methods are given herein, with reference toexemplary types of financial activity. It will be appreciated, however,that pricing methods can be readily adapted to other types of financialactivities, as well. A detailed consideration of one type of pricingstrategy will now be discussed.

Pari-mutuel Market with Endogenous Prices

1. Introduction

Pricing operations are discussed for a pari-mutuel market relating tofirst hurricane landfalls. Other natural peril events could be chosen,as well. Included are a series of binary options for a set of mutuallyexclusive and collectively exhaustive events relating to the location ofthe next U.S. landfalling hurricane at one of 83 coastal segments (mostare individual counties) spanning the U.S. east and Gulf coasts from theMexican to Canadian borders. In the event that no further U.S. hurricanelandfalls occur in a given hurricane season, an 84th event, termed“Null,” is deemed to occur. However, the market structure is moregeneral and could be used to support hedging and speculation in othercontexts also.

This market allows participants to hedge or speculate on the firstcounty where the next hurricane makes landfall in the U.S. by tradingthe options on an exchange, which will be a designated contract marketunder the Commodity Exchange Act. These instruments are commodityoptions—the commodity being defined in exchange rules to be where ahurricane will make landfall first. Under exchange rules, a marketparticipant selects one of the 84 outcomes which the market participantfears (or believes, or both) will be the U.S. county where a hurricanewill first make landfall. That market participant is “long” the countyselected and “short” all the other counties. The market participant paysa premium reflecting this combined “call” on the county selected and“put” on all the other counties. The market participant can lose onlythe amount of the paid premium. If the hurricane makes landfall first inthe county selected, the option holders for that county receive apro-rata share of the combined proceeds from premia received anddeposited with the exchange in a pari-mutuel pool, for all purchases forall counties in that option series. In other words, purchases of optionsin all 84 outcomes fund the payout to the holders of options for thecounty where the hurricane first makes landfall.

Subsequent to sales of “primary” options, as just described, aconventional bilateral bid/ask market in the options can also besupported. Both primary sales and this secondary market can operatesimultaneously, even though the two will be linked to a degree.

2. Mathematical Exposition of the Market Structure

Mathematically, denote the dollar total in the pari-mutuel pool at atime t as M_(t), and denote the number of options that have beenpurchased for county k at time t as N^(k) _(t). When it has beendetermined which of the k=1, . . . , 84 outcomes has occurred, thepayout for each option held in county k is

$\begin{matrix}\begin{matrix}{{W_{t}^{k} = {M_{t}/N_{t}^{k}}},} & {{{if}\mspace{14mu} {the}\mspace{14mu} {storm}\mspace{14mu} {has}\mspace{14mu} {first}\mspace{14mu} {landfall}\mspace{14mu} {at}\mspace{14mu} {county}\mspace{14mu} k}} \\{{= 0},} & {{{otherwise}.}}\end{matrix} & (13)\end{matrix}$

If t=τ, a time at which the landfall outcome (if any) is known, Equation13 specifies the actual payout per option. At previous times, t<τ,Equation 13 specifies the “indicative” payouts; that is, it indicatesthe payout that would be received if no further purchases were to bemade in any of the outcomes, and outcome k were ultimately to occur.

A pari-mutuel market for hurricane landfalls in a given year begins inJanuary, and may extend through the end of hurricane season, on 30November. Because available information about the eventual location ofthe first hurricane landfall will change substantially during thisperiod, it is not appropriate for the option prices to remain static.Rather, the prices are updated dynamically as such information changes,and in particular are determined in proportion to the (time-evolving)probabilities for each of the outcomes. A straightforward and naturalmeasure for the probability of outcome k at any given time, as assessedin aggregate by the market, is the ratio of the premium risked (theprice) to the potential reward (the indicative payout) per option,

$\begin{matrix}{{V_{t}^{k} = {\frac{p_{t}^{k}}{W_{t}^{k}} = \frac{p_{t}^{k}N_{t}^{k}}{M_{t}}}},} & (14)\end{matrix}$

where p_(t) ^(k) is the price paid for an option in outcome k at time t.

Unfortunately, it is not feasible to use the market-assessedprobabilities in Equation 14 for setting prices because of a circularityin definition: Equation 14 specifies market probability as a function ofprice, yet price is determined in proportion to probability. Thisdifficulty is circumvented through the introduction of a set of pricingprobabilities π_(t) ^(k), for the outcomes k at time t. These pricingprobabilities are continually updated in a way that makes them “shadow”the market probabilities in Equation 14. Using these pricingprobabilities π_(t) ^(k), prices are determined according to

$\begin{matrix}\begin{matrix}{{p_{t}^{k} = {\pi_{t}^{k}c\; {\exp \left\lbrack {r\; {j/365}} \right\rbrack}}},} & {\pi_{t}^{k} > \beta} \\{{= {\beta \; c\; {\exp \left\lbrack {r\; {j/365}} \right\rbrack}}},} & {{\pi_{t}^{k} \leq \beta},}\end{matrix} & (15)\end{matrix}$

where c is a constant dollar amount (perhaps c=$1000) called the “par”value; r is an annual interest rate reflecting time value of money,which is introduced in order not to penalize early investors; and jindicates the day of the year (e.g., j=1 for January 1,j=32 for February1, etc.). Here β is a minimum pricing probability, taken to be β=0.0001in the simulations described below. The scaling constant c is called“par” because, if the pari-mutuel market is functioning smoothly, aninvestor purchasing an option for p_(t) ^(k) dollars can expect a payoutin the neighborhood of c dollars if county k receives the firstlandfall.

Optionally, the payout given in Equation 13 can be modified to include a“floor”, or guaranteed minimum payout to holders of options in theoutcome that eventually occurs. In this case, Equation 13 is modified toyield

$\begin{matrix}\begin{matrix}{{W_{t}^{k} = {\max \left( {{Fc},{M_{t}/N_{t}^{k}}} \right)}},} & {{{if}\mspace{14mu} {the}\mspace{14mu} {storm}\mspace{14mu} {has}\mspace{14mu} {first}\mspace{14mu} {landfall}\mspace{14mu} {at}\mspace{14mu} {county}\mspace{20mu} k}} \\{{0,}} & {{{otherwise}.}}\end{matrix} & (16)\end{matrix}$

where the floor F is a guaranteed fraction of the par value, c. In thiscase, the prices in Equation 15 must be modified in order to be able tohonor the floor guarantees, i.e.,

$\begin{matrix}\begin{matrix}{{p_{t}^{k} = {Fc}},} & {{{M_{t}/N_{t}^{k}} \leq {Fc}}} \\{{= {\pi_{i}^{k}c\; {\exp \left\lbrack {r\; {j/365}} \right\rbrack}}},} & {{{{M_{t}/N_{t}^{k}} > {Fc}},{\pi_{t}^{k} > \beta}}} \\{{= {\beta \; c\; {\exp \left\lbrack {r\; {j/365}} \right\rbrack}}},} & {{{{M_{t}/N_{t}^{k}} > {Fc}},{\pi_{t}^{k} \leq {\beta.}}}}\end{matrix} & (17)\end{matrix}$

Of course Equations 16 and 17 reduce to Equations 14 and 15,respectively, when there are no guarantees (F=0).

Before the market is opened, it must be “seeded” with a modest stake ineach of the outcomes. This can be done on the basis of prior (in thecase of the hurricane market, long-term climatological) probabilities π₀^(k). An initial total pool M⁰ is apportioned among the 84 outcomesconsistent with Equations 14 and 15, so that N₀ ^(k)=M₀/c, equally foreach of the k outcomes. The result is congruence between the initialmarket and pricing probabilities, v₀ ^(k)=π₀ ^(k).

The pricing probabilities π_(t) ^(k), are updated each time a newpurchase is made. The time index t in this updating process is notchronological time, but rather is incremented with each individualpurchase, and so is equal at any moment to the total number of optionsthat have been purchased in all counties:

$\begin{matrix}{t = {\sum\limits_{k}{N_{t}^{k}.}}} & (18)\end{matrix}$

Following each purchase of an individual option, the pricingprobabilities for all of the outcomes are updated using an adaptivecontrol algorithm:

$\begin{matrix}\begin{matrix}{{\pi_{t}^{i} = {\pi_{t - 1}^{i} + {\alpha_{t}^{k}{\pi_{t - 1}^{k}\left( {1 - \pi_{t - 1}^{i}} \right)}}}},} & {{i = k}} \\{{= {\pi_{t - 1}^{i}\left( {1 - {\alpha_{t}^{k}\pi_{t - 1}^{k}}} \right)}},} & {{i \neq {k.}}}\end{matrix} & (19)\end{matrix}$

Here the updated pricing probability π_(t) ^(i) at step t for outcome idepends on the pricing probability π_(t-1) ^(k) pertaining to the optionin the outcome (k) that was most recently purchased (at the previoustime, t−1). Accordingly, the first line of Equation 19 is used to updatethe pricing probability for the outcome k most recently purchased, andthe second line is used to update pricing probabilities for all otheroutcomes. Here α_(t) ^(k) is a small adjustment parameter, 0≦α_(t)^(k)<<1, that varies according to the state of the market, as describedbelow. The effect of this updating procedure is that, for α_(t) ^(k)>0,the pricing probability for the outcome in which the last purchase wasmade increases, and the pricing probabilities for the remaining outcomesdecrease. The structure of Equation 19 ensures that the updatedprobabilities are coherent, i.e., 0<π_(t) ^(i)<1 for all outcomes i, andΣ_(i)π_(t) ^(i)=1.

For each new purchase, the adjustment parameter α_(t) ^(k) is chosenaccording to the relationship between the pricing probability π_(t-1)^(k) and the market probability v_(t-1) ^(k) (Equation 14) for theoutcome k just purchased. In particular, α_(t) ^(k) is chosen in orderto move these two probabilities toward equality, allowing the pricingprobabilities π to track, or “shadow” the market probabilities v. Threecases can be distinguished:

Case I: π_(t-1) ^(k)>v_(t-1) ^(k). Here the pricing probability foroutcome k is too high relative to the aggregate market opinion fromEquation 14. This condition can also be diagnosed from the relationshipbetween the indicative payout and the par value (adjusted for time valueof money), since

$\begin{matrix}{{{{\pi_{t - 1}^{k} > v_{t - 1}^{k}} = \frac{\pi_{t - 1}^{k}c\; {\exp \left\lbrack {r\; {j/365}} \right\rbrack}}{W_{t - 1}^{k}}},{{so}\mspace{14mu} {that}}}{W_{t - 1}^{k} > {c\; {{\exp \left\lbrack {r\; {j/365}} \right\rbrack}.}}}} & (20)\end{matrix}$

That is, options for outcome k are overpriced if the indicative payoutis greater than the (interest-adjusted) par value. For this case,increasing the pricing probability for outcome k would produce evengreater separation between the pricing and market probabilities, soα_(t) ^(k)=0 is used in Equation 19, and pricing probabilities for allof the outcomes are unchanged. Any further purchases in outcome k willreduce the indicative payout W^(k) through increases in N^(k), so thatv^(k) will rise toward π^(k). Subsequent purchases in any outcome otherthan k will drive π^(k) downward, toward v^(k).

Case II: Market equilibrium where π_(t-1) ^(k)=v_(t-1) ^(k). Here themarket is in equilibrium before the purchase of the next option t foroutcome k. This purchase will raise the market probability for thisoutcome, v_(t) ^(k)>v_(t-1) ^(k), so the pricing probability π_(t) ^(k)should increase correspondingly. Explicit indication of outcome k usingsuperscripts will be suppressed for notational simplicity). We wish toincrease the pricing probability π_(t), using Equation 19, to match theincrease in v_(t) resulting from the payout dilution for this outcomeproduced by the purchase of one additional option. Therefore,

$\begin{matrix}\begin{matrix}{\pi_{t} = {\pi_{t - 1} + {\alpha_{t}{\pi_{t - 1}\left( {1 - \pi_{t - 1}} \right)}}}} \\{= v_{t}} \\{= \frac{\pi_{t - 1}c\; {\exp \left( {r\; {j/365}} \right)}}{W_{t}}} \\{= \frac{\pi_{t - 1}c\; {\exp \left( {r\; {j/365}} \right)}\left( {N_{t - 1} + 1} \right)}{M_{t - 1} + {\pi_{t - 1}c\; {\exp \left( {r\; {j/365}} \right)}}}} \\{= \frac{\pi_{t - 1}c\; {\exp \left( {r\; {j/365}} \right)}\left( {N_{t - 1} + 1} \right)}{{N_{t - 1}c\; {\exp \left( {r\; {j/365}} \right)}} + {\pi_{t - 1}c\; {\exp \left( {r\; {j/365}} \right)}}}} \\{= {\frac{\pi_{t - 1}\left( {N_{t - 1} + 1} \right)}{N_{t - 1} + \pi_{t - 1}}.}}\end{matrix} & (21)\end{matrix}$

Here use has been made of the fact that, because of the equilibrium atstep t−1, M_(t-1)=N_(t-1) c exp(rj/365). Solving for the equilibriumadjustment parameter,

$\begin{matrix}\begin{matrix}{\alpha_{t} = \frac{\left\lbrack {\frac{\pi_{t - 1}\left( {N_{t - 1} + 1} \right)}{N_{t - 1} + \pi_{t - 1}} - \pi_{t - 1}} \right\rbrack}{\left\lbrack {\pi_{t - 1}\left( {1 - \pi_{t - 1}} \right)} \right\rbrack}} \\{= \frac{\pi_{t - 1}\left\lbrack {\left( {N_{t - 1} + 1} \right) - N_{t - 1} - \pi_{t - 1}} \right\rbrack}{{\pi_{t - 1}\left( {1 - \pi_{t - 1}} \right)}\left( {N_{t - 1} + \pi_{t - 1}} \right)}} \\{= \frac{1}{\left( {N_{t - 1} + \pi_{t - 1}} \right)}} \\{\approx {\frac{1}{N_{t - 1}}.}}\end{matrix} & (22)\end{matrix}$

Since, in all realistic cases N_(t)>>π_(r), the appropriate value forthe adjustment parameter is α_(t) ^(k)=1/N_(t-1) ^(k). Thus, anadditional purchase moves prices relatively little if there are alreadya large number of options in existence for outcome k, but results inlarger price changes if there are relatively few such options. Followingthe algebra in Equation 20, this condition can also be diagnosed fromequality of the indicative payout and the (adjusted) par value.

Case III: π_(t-1) ^(k)<v_(t-1) ^(k). Here the options for outcome k areunder priced, and α_(t) ^(k) should be chosen to adjust π_(t) ^(k)upward. Intuitively, this adjustment should be relatively modest (α_(t)^(k)≈1/N_(t-1) ^(k)) for π_(t-1) ^(k)≈v_(t-1) ^(k), and increase as thediscrepancy between π_(t-1) ^(k) and v_(t-1) ^(k) increases, until amaximum value α_(max) is chosen corresponding to the maximum discrepancybetween π_(t-1) ^(k) and v_(t-1) ^(k). This maximum discrepancy occursfor W_(t-1) ^(k)=Fc. However, the specific form that the function for αshould take between these two endpoints is not clear. Referring now toFIG. 43. two candidate pricing curves for specifying the parameter α, inthe range Fc≦W≦c are shown. FIG. 43 shows two candidate pricing curvefunctions, the consequences of which are explored through simulation inthe next section. A value for α_(max) must also be chosen. When N_(t-1)is small, so that α_(max)/N_(t-1), then α_(t)=1/N_(t-1).

In one example of financial activity according to principles of thepresent invention, equation 19 implements an adaptive control mechanism.Adaptive control here concerns the situation when the exact model of thecontrolled system is not known and has to be ‘learnt on line’ whilecontrolling it. Further information regarding adaptive controlmechanisms is given in: 1) K J Åström, B Wittenmark, Adaptive Control,Addison-Wesley, 1995 2) Narendra, K. S., and Balakrishnan, J. “Adaptivecontrol using multiple models,” IEEE Transaction on Automatic Control,”February 1997, Volume: 42, Issue: 2 pp. 171-187 and 3) Bellman, R., andR. Kalaba, “On Adaptive Control,” IRE Transactions on Automatic Control,November 1959, Volume: 4, Issue: 2, pp. 1-9.

Using first landfall of hurricanes as one example, it is preferred touse an adaptive algorithm that “learns” as it works, and repricesoptions in multiple regions according to probabilities that the market“believes” to reflect the landfall risks, which are themselvesinfluenced by meteorological forecasts for hurricane activity. Theadaptive control mechanism is preferred in a one-sided market, ratherthan a traditional bilateral market where there are both buyers andsellers. When changes in forecast information become available to theparticipants in this financial activity (such as updates providing forchanges in a hurricane's potential landfall area, direction of movement,wind speed, strength, etc.), the pricing algorithm is able to reactquickly to the resulting changes in investment positions as selected bythe participants. For example, as a hurricane becomes closer tolandfall, the algorithm reacts to relatively higher buying levels forthe now-more-likely outcomes, by raising prices to appropriate newlevels for those outcomes. Otherwise, earlier investors in thoseoutcomes will be disadvantaged as later buyers with better or morerecent information, to extract value from those early investors bybuying more cheaply into a given location than is justified. This typeof monitor is not preferred in bilateral markets because, wheninformation changes such that an asset has more value than before,potential sellers will hold out for higher (new) prices rather thansettling for the lower (old) price.

Optionally, in another variation, the adjustment parameter alpha inEquation 19 could be defined as a decreasing function of the number ofoptions, Nk, that have been previously purchased in county k. In oneimplementation, since Equation 22 shows that alpha should decrease ininverse proportion to Nk, alpha would be defined as the quotient of afixed constant divided by Nk. This fixed constant is chosen to be largerthan 1 (the value implied by Equation 22), in order for the resultingprices to be able to respond quickly to deviations from marketequilibrium, such as might be brought on by changes in meteorologicalcircumstances that would make some counties more likely, and somecounties less likely, targets than previously.

3. Simulation Example

This section describes stochastic simulations of the pari-mutuelhurricane market, using the 2004 hurricane season through the firstlandfall of Hurricane Charley, as an example. That is, the 2004hurricane season is simulated many times, using different random butconceptually reasonable sequences of investments in the variouscounties. Charley formed in the eastern Caribbean, and tracked south ofJamaica and over western Cuba before making landfall on the west coastof Florida, at Lee county, on 13 August.

The overall flow of money into the pari-mutuel pool is taken as thefixed but plausible sequence shown in Table 4 (see FIG. 46), withfigures in millions. Here it is assumed that the initial seeding is $2M,averaging about $25K per each of the 84 outcomes. Table 4 specifiesstrong investment interest from January through mid-February, with arelative lull until May, and then an increase again near the beginningof hurricane season on 1 June. During the hurricane season, investmentinterest increases beginning on 31 July. The tropical depression thatbecomes hurricane Alex materializes on 31 July, but does not makelandfall. The tropical depression that will become tropical storm Bonniefirst appears on 3 August. The tropical depression that will becomehurricane Charley first appears on 9 August. The dollar total in thepool when closed by the approach of Hurricane Charley on 12 August is$2B, of which about ⅓ has been invested before the beginning ofhurricane season on 1 June, and ⅔ during hurricane season.

This assumed daily sequence of dollar flows is a very challenging onefor the algorithm, on two counts. First, the initial seeding is verylight relative to the funds coming into the pool during the first twoweeks, so that substantial price volatility is expected. Second, 45% ofthe eventual $2B pours into the fund during the last two days inresponse to the imminent landfall of Hurricane Charley. These newpurchases are concentrated in counties on the west coast of Florida, sothe internal market probabilities v must respond very quickly to theevent if the eventual payout W_(τ) at Lee county is to be maintainednear the par value.

The simulation time step is once daily, meaning that during hurricaneseason only one of the 6-hourly NHC advisories is used to forecast themeteorological risks of first landfall. From 31 July through 2 Augustthese are for Alex, from 3 August through 8 August these are for Bonnie,and for 9 August through 12 August these are for Charley. For eachsimulated 2004 season, the dollars specified for each day in Table 4 areallocated to the 84 outcomes according to a combination ofmeteorological risks and random factors. Specifically, let D(j) be thedollars invested over the entire pool on day j, from the middle columnin Table 4. Define g_(k)(j) to be the random relative allocation of D(j)to county k on day j, so that the money invested in county k on day j is

$\begin{matrix}{{m_{k}(j)} = {\frac{g_{k}(j)}{\sum\limits_{i = 1}^{84}{g_{i}(j)}}{{D(j)}.}}} & (23)\end{matrix}$

The random relative allocations g_(k)(j) are gamma-distributed randomvariables, with mean

μ_(k)(j)=ω_(k)(j)  (24)

where ω_(k)(j) is the forecast probability for county k on day j. Thegamma distributions from which the relative dollar allocations g_(k)(j)are drawn have common coefficient of variation (i.e., standard deviationdivided by mean) CV=½, which is independent of both time and county. Theresult is that simulated investments in counties exhibiting stronger(mean) buying interest on a given day will be more variable from run torun of the simulation. This effect is especially strong during the lastfew days of the simulation, in which the ω_(k)(j) are relatively largefor the counties on the west coast of Florida.

Having defined the dollar allocations on each day, the numbers ofoptions bought for each of the 84 outcomes are determined using themathematics in Section 2. For the specific results reported here, fixedvalues are taken for the parameters F=0.5, r=0.05, and β=0.0001. Theeffects of each of the pricing curves labeled “full logistic” and “halflogistic” in FIG. 43 are investigated, using values of α_(max) rangingfrom 0.00001 through 0.005. In addition, three levels of overall buyingvolume are simulated through variation in the par value. For c=$1000relatively large (τ≈1.8×10 ⁸) numbers of options are purchased overallin a given simulated year. An order of magnitude fewer (τ≈1.8×10⁷)options are purchased for c=$10000; and still fewer (τ≈1.8×10⁶) areneeded when and c=$10000 but all the dollar amounts in Table 4 reducedby a factor of 10. For each combination of parameter values, 100simulated years are calculated.

In order to induce disequilibrium in the simulated market, options arebought in lots, rather than individually, even though prices arerecalculated after each individual purchase, as per Equation 19. Afterrandom allocation of the day's investment dollars to each county usingEquations 21 and 22, the number of options that could be purchased foreach county are calculated, using prices for the end of the previousday. The lot size for each county for the upcoming day is then 1/50 ofthe median of these numbers of options. Having chosen this lot size forthe day, the simulation program randomly chooses among the counties forwhich the day's dollars have not yet been exhausted, and buys one lot.The result is that counties that have a relatively small random dollarallocation for the day are finished early, so that toward the end of asimulated day the buys are concentrated in the few counties withrelatively large random allocations. This procedure simulates the effectof a few large players investing large sums into those counties with thelarger random allocations for the day.

Referring now to FIG. 44, an example time series of prices for Leecounty, and the adjacent but smaller Charlotte county, are shown for onemodel realization of the pari-mutuel market. Horizontal dash-dot linesthrough 30 July indicate the product of the respective forecastprobabilities ω and the par value of c $10,000 (τ≈1.8×10⁷), toward whichthe market prices should move as they recover from random perturbationsduring this time period. January volatility results from the initialseeding being small relative to the large sequence of early investments.Large price increases in mid-August reflect the large sums beinginvested in counties on the west coast of Florida as Charley approaches.Prices for the final two days are offscale, and are not plotted forclarity in showing the rest of the time series. The half-logisticpricing curve with α_(max)=0.0005 has been used.

FIG. 44 shows time series of prices for one of the 100 realizationsproduced with c=$10,000 (τ≈1.8×10⁷), using the half-logistic pricingcurve with α_(max)=0.0005. Prices are shown for Lee county (red), andthe adjacent but smaller Charlotte County (black). The dash-dot linesindicate the levels, given by the product ωc, toward which the pricesshould move as they recover from random perturbations, during the period1 January through 30 July. Appreciable price volatility is evident inJanuary as the market responds to the very large sums, relative to thesmall initial seeding, that are invested during that time. Subsequently,until the meteorological probabilities ω change on 31 July, theseinternally generated market prices correctly track the levels that theyshould move toward (given the dollar allocations specified by Equations21 and 22), confirming the stability of the internal pricing mechanismdescribed above.

FIG. 45 shows average payouts and price volatility for Lee county, using(a) the full logistic, and (b) the half logistic pricing curves fromFIG. 43; as functions of the adjustment parameter α_(max). Volatility iscalculated as the standard deviation of end-of-day prices between 11January and 30 July, averaged over the 100 realizations for eachparameter combination. Parameter combinations for which the averagepayouts (solid lines) are near the par value reflect good functioning ofthe market. Values of α_(max) that are too small result in averagepayouts that are unacceptably small, as a result of prices not adjustingsufficiently quickly to the large flux of money into the market duringthe last two simulated days. Reduced average payouts for large values ofα_(max), reflect price increases that are too strong, with the resultthat prices for other counties decrease too much, allowing payoutdilution. Not surprisingly, volatility (dashed lines) increasesmonotonically with increases in α_(max). Therefore, the optimal α_(max),appears to be a compromise between prices responding quickly enough tomaintain payouts near par, versus responding slowly enough to suppressexcessive price volatility.

Referring now to FIG. 45, average payouts (solid) and volatility(dashed) for Lee County, are shown using (a) the full logistic, and (b)the half-logistic pricing curves shown in FIG. 42, as functions of theadjustment parameter α_(max). All quantities are expressed as a fractionof the par value, c.

The simulated market responses to the two pricing curves from FIG. 43are similar, but overall results for the half-logistic pricing curve(FIG. 45 b) exhibit lesser sensitivity to choice of α_(max) and lowerprice volatility overall. Both panels in FIG. 45 exhibit a dependence ofmarket response on the overall volume, τ, suggesting that a betterpricing curve than either of the two shown in FIG. 43 could probably befound. However, these results indicate that choosing the half-logisticpricing curve together with α_(max)=0.0005 yields a market that behaveswell over a wide range of possible conditions.

In these simulations, threatened breaches of the payout floor Fc,requiring implementation of the first line of Equation 17 for pricing,occurred only in the first 2 weeks of the simulated years, or during thelast few days. For the most part, parameter combinations yieldingaverage payouts within 80% to 85% of par exhibited few or no suchthreatened breaches in August. Between these two difficult times, thesimulated market was well able to adjust internally to the day-to-dayvariations in the amounts invested and their relative random allocationsamong the counties.

The price volatility and threatened floor breaches occurring very earlyin the simulations are nearly unavoidable given the relatively quitesmall initial seeding of the market. Clearly these would be smaller ifearly investment interest is not as large as assumed here, and of coursecould be reduced by seeding the pool with a larger initial sum. However,a less costly and likely more profitable approach would be for theseeding agency to monitor early market performance closely, and act tosuppress the price volatility that leads to threatened floor breaches bybuying the most under priced counties. Stability could be ensured inthis way through purchase of relatively few of the 84 outcomes, and atprices that would be very favorable relative to their eventual expectedpayouts.

Application of Pari-Mutuel Market With Endogenous Prices to FirstHurricane Landfalls 4.1. Introduction

Operation of a pari-mutuel market involving another series of binaryoptions for a set of mutually exclusive and collectively exhaustiveevents is discussed. This operation is similar in some ways to theoperations set out in Section 1 above, but presents the operator of thefinancial activity with a number of different options. These events alsorelate to the location of the next U.S. landfalling hurricane at one of83 coastal segments (most are individual counties) spanning the U.S.east and Gulf coasts from the Mexican to Canadian borders. In the eventthat no further U.S. hurricane landfalls occur in a given hurricaneseason, an 84th event, termed “Null,” is deemed to occur.

The market structure herein is also more general and could be used tosupport hedging and speculation in other contexts. For example, thismarket structure allows participants to hedge or speculate on the firstcounty where the next hurricane makes landfall in the U.S. by tradingthe options on an exchange, which will be a designated contract marketunder the Commodity Exchange Act. These instruments are commodityoptions—the commodity being defined in exchange rules to be where ahurricane will make landfall first.

Under exchange rules, a market participant selects one of the 84outcomes which the market participant fears (or believes, or both) willbe the U.S. county where a hurricane will first make landfall. Thatmarket participant is “long” the county selected and “short” all theother counties. The market participant pays a premium reflecting thiscombined “call” on the county selected and “put” on all the othercounties. The market participant can lose only the amount of the paidpremium. If the hurricane makes landfall first in the county selected,the option holders for that county receive a pro-rata share of thecombined proceeds from premia received and deposited with the exchangein a pari-mutuel pool, for all purchases for all counties in that optionseries. In other words, purchases of options in all 84 outcomes fund thepayouts to the holders of options for the county where the hurricanefirst makes landfall.

Additionally, a “floor” on the payout to option holders in the affectedcounty can be supported, which is expected to be especially appealing toretail investors who would enter the market to hedge against actualproperty- and other storm-related losses. Under this mechanism, aparticipant's hedge against hurricane landfall in a particular countycan be guaranteed a minimum monetary return, conditional on landfall inthat county, which amount would be specified at the time of theinvestment. The pricing algorithm is structured such that thepari-mutuel payouts, including these conditional guarantees, areentirely self-funded, so that the exchange assumes no risk.

Subsequent to sales of “primary” options, as just described, aconventional bilateral bid/ask market in the options can also besupported. Both primary sales and this secondary market can operatesimultaneously, even though the two will be linked to a degree.

4.2. Mathematical Exposition of the Market Structure

The dollar total in the pari-mutuel pool at a time t is denoted asM_(t), and the number of options that have been purchased for county kat time t are denoted as N^(k) _(t). Upon been determination of which ofthe 84 outcomes has occurred, the payout for each option held for thatoutcome is

$\begin{matrix}\begin{matrix}{{W_{t}^{k} = {M_{t}/N_{t}^{k}}},} & {{{if}\mspace{14mu} {the}\mspace{14mu} {storm}\mspace{14mu} {has}\mspace{14mu} {first}\mspace{14mu} {landfall}\mspace{14mu} {at}\mspace{14mu} {county}\mspace{14mu} k}} \\{{= 0},} & {{{otherwise}.}}\end{matrix} & (25)\end{matrix}$

If t=τ, a time at which the landfall outcome (if any) is known, Equation25 specifies the actual payout per option. At previous times, t<τ,Equation 25 specifies the “indicative” payouts; that is, it indicatesthe payout that would be received if no further purchases were to bemade in any of the outcomes, and outcome k were ultimately to occur.

A pari-mutuel market for hurricane landfalls in a given year begins inJanuary, and may extend through the end of hurricane season, on 30November. Because available information about the eventual location ofthe first hurricane landfall will change substantially during thisperiod, it is not appropriate for the option prices to remain static.Rather, the prices are updated dynamically as such information changes,and in particular as market activity adjusts to the changinginformation, as reflected by a set of time-evolving “pricingprobabilities” τ_(t) ^(k) for the outcomes k at time t. FIG. 41,discussed below, shows an example of a display of such information to aninvestor, along with other data. These pricing probabilities arecontinually updated in a way that makes them converge toward, or“shadow,” the aggregate market opinion of the outcome probabilities,according to an algorithm that will be described shortly. Using thesepricing probabilities τ_(t) ^(k), prices are determined according to

$\begin{matrix}\begin{matrix}{{p_{t}^{k} = {\pi_{t}^{k}c\; {\exp \left\lbrack {r\; {j/365}} \right\rbrack}}},} & {{\pi_{t}^{k} > \beta}} \\{{= {\beta \; c\; {\exp \left\lbrack {r\; {j/365}} \right\rbrack}}},} & {{{\pi_{t}^{k} \leq \beta},}}\end{matrix} & (26)\end{matrix}$

where c is a constant dollar amount (perhaps c=$1000) called the “par”value; r is an annual interest rate reflecting time value of money,which is introduced in order not to penalize early investors; and jindicates the day of the year (e.g., j=1 for January 1, j=32 forFebruary 1, etc.). Here β is a minimum pricing probability, taken to beβ=0.0001 in the simulations described below. The scaling constant c iscalled “par” because, if the pari-mutuel market is functioning smoothly,an investor purchasing an option for p_(t) ^(k) dollars can expect apayout in the neighborhood of c dollars if county k receives the firstlandfall.

Optionally, the payout given in Equation 25 can be modified to include a“floor”, or guaranteed minimum payout to holders of options in theoutcome that eventually occurs. In this case, Equation 25 is modified toyield

$\begin{matrix}\begin{matrix}{{W_{t}^{k} = {\max \left( {{Fc},{M_{t}/N_{t}^{k}}} \right)}},} & {{{{if}\mspace{14mu} {the}\mspace{14mu} {storm}\mspace{14mu} {has}\mspace{14mu} {first}\mspace{14mu} {landfall}\mspace{14mu} {at}\mspace{14mu} {county}\mspace{20mu} k},}} \\{{0,}} & {{{otherwise}.}}\end{matrix} & (27)\end{matrix}$

where the floor F is a guaranteed fraction of the par value, c. In thiscase, the prices in Equation 26 must be modified in order to be able tohonor the floor guarantees, i.e.,

$\begin{matrix}\begin{matrix}{{p_{t}^{k} = {\pi_{t}^{k}c\; {\exp \left\lbrack {r\; {j/365}} \right\rbrack}}},} & {{{{M_{t}/N_{t}^{k}} > {Fc}},{\pi_{t}^{k} > \beta}}} \\{{= {\beta \; c\; {\exp \left\lbrack {r\; {j/365}} \right\rbrack}}},} & {{{{M_{t}/N_{t}^{k}} > {Fc}},{\pi_{t}^{k} \leq \beta}}} \\{{= {Fc}},} & {{{M_{t}/N_{t}^{k}} \leq {{Fc}.}}}\end{matrix} & (28)\end{matrix}$

Of course Equations 27 and 28 reduce to Equations 25 and 26,respectively, when there are no guarantees (F=0).

Before the market is opened, it must be “seeded” with a modest stake ineach of the outcomes. This can be done on the basis of prior (in thecase of the hurricane market, k long-term climatological) probabilitiesπ₀ ^(k). An initial total pool M₀ is apportioned among the 84 outcomesconsistent with the initial pricing probabilities quantifying the risk,given by the ratio of price to indicative payout,

$\begin{matrix}{\pi_{0}^{k} = {\frac{p_{0}^{k}}{W_{0}^{k}} = {\frac{\pi_{0}^{k}c\; N_{0}^{k}}{M_{0}}.}}} & (29)\end{matrix}$

Thus, N₀ ^(k)=M₀/c, equally for each of the k outcomes.

The pricing probabilities π_(t) ^(k), are updated each time a newpurchase is made. The time index t in this updating process is notchronological time, but rather is incremented with each individualpurchase, and so is equal at any moment to the total number of optionsthat have been purchased in all counties:

$\begin{matrix}{t = {\sum\limits_{k}{N_{t}^{k}.}}} & (30)\end{matrix}$

Following each purchase of an individual option, the pricingprobabilities for all of the outcomes are updated using a variant of theRobbins-Monro stochastic approximation algorithm:

$\begin{matrix}\begin{matrix}{{\pi_{t}^{i} = {\pi_{t - 1}^{i} + {\alpha_{t}^{k}{\pi_{t - 1}^{k}\left( {1 - \pi_{t - 1}^{i}} \right)}}}},} & {{i = k}} \\{{= {\pi_{t - 1}^{i}\left( {1 - {\alpha_{t}^{k}\pi_{t - 1}^{k}}} \right)}},} & {{i \neq {k.}}}\end{matrix} & (31)\end{matrix}$

This is an adaptive control mechanism, in which the aggregate of marketopinion regarding (the possibly time-evolving) probabilities for each ofthe possible outcomes is learned in response to the sequence ofpurchases made by market participants. Here the updated pricingprobability π_(t) ^(i) at step t for outcome i depends on the pricingprobability π_(t-1) ^(k) pertaining to the option in the outcome (k)that was most recently purchased (at the previous time, t−1).Accordingly, the first line of Equation 31 is used to update the pricingprobability for the outcome k most recently purchased, and the secondline is used to update pricing probabilities for all other outcomes.Here α_(t) ^(k) is a small adjustment parameter, 0<α_(t) ^(k)<<1, thatvaries according to the state of the market, as described below. Theeffect of this updating procedure is that the pricing probability forthe outcome in which the last purchase was made increases, and thepricing probabilities for the remaining outcomes decrease. The structureof Equation 31 ensures that the updated probabilities are coherent,i.e., 0<π_(t) ^(i)<1 for all outcomes i, and Σ_(i)π_(t) ^(i)=1.

For each new purchase, the adjustment parameter α_(t) ^(k) is inverselyproportional to the number of options previously purchased in thatoutcome,

$\begin{matrix}{\alpha_{t}^{k} = {\frac{H}{N_{t}^{k}}.}} & (32)\end{matrix}$

If few options have been bought previously, then an additional purchasewill move prices relatively more than if many options are already inexistence. Section 4.4 below shows that, if the market is inequilibrium, H=1 in Equation 32. However, in practice one should chooseH>1 in order for prices to be able to respond quickly to deviations frommarket equilibrium, such as might be brought on by changes in externalinformation (e.g., the meteorological situation) relevant to the market.Simulations indicate that 30≦H≦40 produce a smoothly operating marketwith relatively small price volatility.4.3. Simulation Example This section describes stochastic simulations ofthe pari-mutuel hurricane market, using the 2004 hurricane seasonthrough the first landfall of hurricane Charley as an example. That is,the 2004 hurricane season is simulated many times, using differentrandom but conceptually reasonable sequences of investments in thevarious counties. Charley formed in the eastern Caribbean, and trackedsouth of Jamaica and over western Cuba before making landfall on thewest coast of Florida, at Lee county, on 13 August.

The overall flow of money into the pari-mutuel pool is taken as thefixed but plausible sequence shown in Table 5, with figures in millions.Here it is assumed that the relatively small initial seeding is $2M,averaging about $25K per each of the 84 outcomes. Table 5 specifiesstrong investment interest from January through mid-February, with arelative lull until May, and then an increase again near the beginningof hurricane season on 1 June. During the hurricane season, investmentinterest increases beginning on 31 July. The tropical depression thatbecomes hurricane Alex materializes on 31 July, but does not makelandfall. The tropical depression that will become tropical storm Bonniefirst appears on 3 August. The tropical depression that will becomehurricane Charley first appears on 9 August. The dollar total in thepool when further investment in this option series is closed by theapproach of Hurricane Charley on 12 August is $2B, of which about ⅓ hasbeen invested before the beginning of hurricane season on 1 June, and ⅔during hurricane season.

This assumed daily sequence of dollar flows is a very challenging onefor the pricing algorithm, on two counts. First, the initial seeding isvery light relative to the funds coming into the pool during the firsttwo weeks, so that substantial price volatility is expected initially.Second, nearly a quarter of the eventual $2B pours into the fund duringthe last two days in response to the imminent landfall of hurricaneCharley. These new purchases are concentrated in counties on the westcoast of Florida, so the pricing probabilities must respond very quicklyto the event if the eventual payout W_(τ) at Lee county is to bemaintained near the par value.

The simulation time step is once daily, meaning that during hurricaneseason only one of the 6-hourly NHC advisories is used to forecast themeteorological risks of first landfall. From 31 July through 2 Augustthese are for Alex, from 3 August through 8 August these are for Bonnie,and for 9 August through 12 August these are for Charley. For eachsimulated 2004 season, the dollars specified for each day in Table 5 areallocated to the 84 outcomes according to a combination ofmeteorological risks and random factors. Specifically, let D(j) be thedollars invested over the entire pool on day j, from the middle columnin Table 5. Define g_(k)(j) to be the random relative allocation of D(j)to county k on day j, so that the money invested in county k on day j is

$\begin{matrix}{{m_{k}(j)} = {\frac{g_{k}(j)}{\sum\limits_{i = 1}^{84}{g_{i}(j)}}{{D(j)}.}}} & (33)\end{matrix}$

The random relative allocations g_(k)(j) are gamma-distributed randomvariables, with mean

μ_(k)(j)=ω_(k)(j),  (34)

where ω_(k)(j) is the forecast probability for county k on day j. Thegamma distributions from which the relative dollar allocations g_(k)(j)are drawn have common coefficient of variation (i.e., standard deviationdivided by mean) CV=½, which is independent of both time and county. Theresult is that simulated investments in counties exhibiting stronger(mean) buying interest on a given day will be more variable from run torun of the simulation. This effect is especially strong during the lastfew days of the simulation, in which the ω_(k)(j) are relatively largefor the counties on the west coast of Florida.

Having defined the dollar allocations on each day, the numbers ofoptions bought for each of the 84 outcomes are determined using themathematics in Section 4.2. For the specific results reported here,fixed values are taken for the parameters F=0.5, r=0.05, and β=0.0001.The parameter H, controlling the step size in the adaptive control ofprices, is varied through the range 1-100. In addition, four levels ofoverall buying volume are simulated through variation in the par value.For c=$100 a very large (τ≈1.8×10⁹) number of options is purchasedoverall in a given simulated year. An order of magnitude fewer(τ≈1.8×10⁸) options are purchased for c=$1000; and still fewer (1.8×10⁷and 1.8×10⁶) are needed when and c=$10,000 and $100,000, respectively.For each combination of parameter values, 100 simulated years arecalculated.

Simulated option purchases are made in lots, rather than individually,even though prices are recalculated after each individual purchase, asper Equation 31. After random allocation of the day's investment dollarsto each county using Equations 33 and 34, the number of options thatcould be purchased for each county are calculated, using prices for theend of the previous day. The lot size for each county for the upcomingday is then 1/50 of the median of these numbers of options. Havingchosen this lot size for the day, the simulation program randomlychooses among the counties for which the day's dollars have not yet beenexhausted, and buys one lot. The result is that counties that have arelatively small random dollar allocation for the day are finishedearly, so that toward the end of a simulated day the buys areconcentrated in the few counties with relatively large randomallocations. This procedure simulates the effect of a few large marketparticipants investing large sums into those counties with the largerrandom allocations for the day.

FIG. 44 shows a time series of prices for one of the 100 realizationsproduced with c=$1000 (τ≈1.8×10⁸), using H=30. Prices are shown for Leecounty, and the adjacent but smaller Charlotte County. The dash-dotlines indicate the levels, given by the product ωc, toward which theprices should move as they recover from random perturbations, during theperiod 1 January through 30 July. Appreciable price volatility isevident in January as the market responds to the very large sums,relative to the small initial seeding, that are invested during thattime. Subsequently, until the meteorological probabilities (ω=0.0106 forLee county, and (ω=0.0021 for Charlotte county) change on 31 July, theseinternally generated market prices correctly track the levels that theyshould move toward (given the random dollar allocations specified byEquations 33 and 34), confirming the stability of the internal pricingmechanism described in Section 4.2. Similarly, on the final two days ofthe simulation, the respective meteorological probabilities for Lee andCharlotte counties are approximately 0.11 and 0.04, and the pricesadjust quite rapidly to levels consistent with these values.Importantly, the pricing algorithm is able to recover from the initialvolatility that arises because of the very thin initial seeding, andconverge toward the simulated market consensus “opinion,” even thoughthat is masked by considerable randomness in the allocation ofinvestments among the counties. The initial volatility could be reducedby a larger initial seeding of the market, but this example emphasizesthe robustness of the pricing adaptation algorithm in Equation 31. Thisinitial volatility could also be reduced by introducing a ceiling on theparameter α, although probably at the expense of a more frequent need toinvoke the payout floor protection (third line of Equation 28).

FIG. 44 shows a time series of prices for Lee county, and the adjacentbut smaller Charlotte county, during one model realization of thepari-mutuel market. Horizontal dash-dot lines through 30 July indicatethe product of the respective forecast probabilities ω and the par valueof c=$1000 (τ≈1.8×10⁸), toward which the market prices should move asthey recover from random perturbations during this time period. Januaryvolatility results from the initial seeding being small relative to thelarge sequence of early investments. Large price increases in mid-Augustreflect the large sums being invested in counties on the west coast ofFlorida as Charley approaches. H=30 has been used in Equation 32.

Table 6 shows the effect on market performance of different choices forthe parameter H, in connection with different overall levels of marketvolume (controlled by different choices for the par, c). Tabulated areaverage returns for Lee county, as a fraction of par, and standarddeviation of these returns over 100 simulated years, although similarresults are obtained for the other counties also. Defining theadjustment parameter α in Equation 31 as being inversely proportional toN^(k) results in similar average returns for a given value of H,regardless of the level of overall volume. In contrast, when a constantvalue for α is used (i.e., no dependence on N^(k), results not shown),larger α's are needed when market volume is small, and smaller α's areneeded when market volume is large.

For the larger values of H in Table 6 the standard deviation of payoutcan be rather large. For the smaller values of H the price adjustmentsrespond too slowly to the large influx of investment into the westernFlorida counties in the final days of the simulation, so that thepari-mutuel pool is diluted by the rush of late investment that isallowed at prices that are too low, and accordingly average payouts aresubstantially below par. This dilution does not occur for moderatevalues of H, indicating that the market mechanism is resistant tomanipulation attempts when the pricing adjustment parameter is definedappropriately. The very large investments in the final two daysspecified in Table 5 can be interpreted as simulating the actions oflarge speculators seeking to profit from overwhelming the market justbefore the hurricane landfall. But for such attempts to be successful itwould be necessary for them to extract value from earlier investors, sothat payouts near par imply failure of this manipulation strategy.

Asterisks in Table 6 indicate parameter combinations for which the 50%payout floor was never challenged in any of the 100 simulated years (forany of the counties, not just Lee), which would have required use of thethird line of Equation 28. “Plus” symbols in Table 6 indicate threecases where the 50% floor was challenged for a single county, during thefirst few days of January. Together, these cases coincide with the rangeof H for which minimum payout variability is also achieved throughoutthe range of overall market volumes.

Finally, the rightmost column in Table 6 shows price volatility for Leecounty, measured as the standard deviation of end-of-day prices for theperiod 11 January (to exclude early, very high price volatility derivingfrom the light initial market seeding) through 30 July (just before thefirst tropical depression is declared, changing the meteorologicalprobabilities), and averaged over the 100 simulated years. These areshown only for c=$100, but results for other cases are comparable. Notsurprisingly, the volatility increases monotonically with H, since thestep size in the price adjustment algorithm (Equation 31) increases withH. The optimal H will be large enough for average payouts to be nearpar, but as small as possible consistent with this condition in order tominimize price volatility. The results in Table 6 suggest that 30<H<40is an appropriate range. A typical screen display presenting investmentinformation to an investor is shown in FIG. 41.

4.4 Derivation of the Correct Adjustment Parameter α at EconomicEquilibrium

This section treats the case of a market in equilibrium, in whichEquation 29 holds at time t−1 for all outcomes k. In this section,explicit indication of outcome k using superscripts will be suppressedfor notational simplicity.

Let v_(t)=p_(t)/W_(t) be the outcome probability implied by the ratio ofrisk (price) to potential reward (indicative payout), as in Equation 29.In one example, the objective is to increase the pricing probabilityπ_(t), using Equation 31, to match the increase in v_(t) resulting fromthe payout dilution for this outcome produced by the purchase of oneadditional option. Therefore,

$\begin{matrix}\begin{matrix}{\pi_{t} = {\pi_{t - 1} + {\alpha_{t}{\pi_{t - 1}\left( {1 - \pi_{t - 1}} \right)}}}} \\{= v_{t}} \\{= \frac{\pi_{t - 1}c\mspace{14mu} {\exp \left( {{rj}/365} \right)}}{W_{t}}} \\{= \frac{\pi_{t - 1}c\mspace{11mu} {\exp \left( {{rj}/365} \right)}\left( {N_{t - 1} + 1} \right)}{M_{t - 1} + {\pi_{t - 1}c\; {\exp \left( {{rj}/365} \right)}}}} \\{= \frac{\pi_{t - 1}c\mspace{11mu} {\exp \left( {{rj}/365} \right)}\left( {N_{t - 1} + 1} \right)}{{N_{t - 1}c\mspace{11mu} {\exp \left( {{rj}/365} \right)}} + {\pi_{t - 1}c\mspace{11mu} {\exp \left( {{rj}/365} \right)}}}} \\{= {\frac{\pi_{t - 1}\left( {N_{t - 1} + 1} \right)}{N_{t - 1} + \pi_{t - 1}}.}}\end{matrix} & (35)\end{matrix}$

Here use has been made of the fact that, because of the equilibrium atstep t−1, M_(t-1)=N_(t-1) c exp(rj/365). Solving for the equilibriumadjustment parameter,

$\begin{matrix}\begin{matrix}{\alpha_{t} = {\left\lbrack {\frac{\pi_{t - 1}\left( {N_{t - 1} + 1} \right)}{N_{t - 1} + \pi_{t - 1}} - \pi_{t - 1}} \right\rbrack/\left\lbrack {\pi_{t - 1}\left( {1 - \pi_{t - 1}} \right)} \right\rbrack}} \\{= \frac{\pi_{t - 1}\left\lbrack {\left( {N_{t - 1} + 1} \right) - N_{t - 1} - \pi_{t - 1}} \right\rbrack}{{\pi_{t - 1}\left( {1 - \pi_{t - 1}} \right)}\left( {N_{t - 1} + \pi_{t - 1}} \right)}} \\{= {\frac{1}{\left( {N_{t - 1} + \pi_{t - 1}} \right)} \approx {\frac{1}{N_{t - 1}}.}}}\end{matrix} & (36)\end{matrix}$

This final approximation will be a very close one, because in realisticcases N_(t)>>π_(t).

Considerations Regarding Payout

In general, the basis or methodology of the payout can be eitherpari-mutuel or non pari-mutuel (e.g. a fixed or a varying payout price,such as one based on a scale or index). As a further alternative, payoutcan be structured on a modified pari-mutuel basis. For example, a poolof money can be split (after recovering overhead costs) among thequalifying participants in an unequal, i.e. modified manner, depending,in one instance, on an algorithm, or on a scale or index or in anotherinstance, on a requirement to fund an expected minimum payout, or“floor,” as will be discussed herein.

If desired, financial activities relating to hurricane natural perilevents can be structured around hurricane landfall or hurricane landtracks, either individually, one exclusive of the other, or incombination. A question arises, for example when a hurricane landfall ismade on or close to a border between two unit areas (i.e. geographicalareas, such as counties used to define purchase units). An arbitrarywidth can be assigned to the point of landfall if desired, by theprovider of the financial activity.

The passage of a hurricane over inland geographical areas can raise anumber of different possibilities made available to the provider of afinancial activity. For example, if the National Hurricane Center isdesignated as the external objective independent information source, onereport currently available to providers of financial activities is theso-called “best track” report which issues after a hurricane event isconcluded. The “best track” report defines the inland path of ahurricane according to a table of discrete position values. Thus, it isleft to the provider of the financial activity to determine the best wayto define the hurricane path between published points on the “besttrack” table. If desired, the points of the “best track” table can beconnected by straight lines or by curved lines according to a predefinedcurve-fitting method, for example. As a further possibility, anarbitrary width can be assigned to the hurricane path.

If desired, other sources of information can be employed since the “besttrack” report is not the only possible source of scoring information,and may not be desirable in certain instances because of the time delayassociated with issuance of the report after conclusion of the naturalactivity. For example, the same kind of information (lat/lon and maximumsustained winds) are available in near-real time in what are called“advisories” issued by the National Hurricane Center, which do notsuffer from prolonged time delays. Preferably, the most rapidsatisfactory resolution of the outcome of the natural peril event ispreferred, so that distributions can be made promptly to individuals whosuffer from the natural peril event.

For other types of natural activity, such as tornadoes, the path and/orintensity can be reported by an official source, and for earthquakes,the path of damage and intensity can be specified according to anindependent third party.

Different possibilities are presented when considering a particulargeographical land unit. For example, payout for a geographical land unitcan be based upon one or more external factors, such as a simplehit/no-hit treatment for the land unit of interest. In another example,payout for a land unit of interest can be based upon the publishedstrength of the hurricane according to the “best track” or other table.As a further possibility, it is recognized that the strength of ahurricane can vary in intensity or strength when passing over a givengeographical land unit of interest. The possibility is thus presentedfor a mathematical treatment taking into account the difference ofstrengths at entry and exit points of the hurricane with respect to thegeographical unit of interest. As a further possibility, thegeographical unit of interest can lie between points published on the“best track” table, and some manner of interpolation of values can bemade with respect to the geographical unit of interest. If desired,payouts can be calculated based upon the strength of the hurricane forthe qualifying geographical unit. For example, one payout possibility isto award greater payout for geographical units suffering greaterstrengths of hurricane activity, under the premise that more help willbe provided for those participants that suffer greater damage, asmeasured by hurricane strength.

Variability factors other than those presented above can also beconsidered when calculating payouts to qualifying participants. Forexample, in addition to timing factors and probability factors discussedabove (which are preferably employed for price variability as well aspayout variability) an account can be made of the residence time of ahurricane in a given geographical unit of interest, under the premiseagain that more help will be provided for those participants that suffergreater damage as measured by the time that a hurricane is present in agiven geographical unit of interest.

It is sometimes preferred to provide an expectation of a minimum payoutor “floor” for participants that suffer damage from a hurricane or othernatural peril event. The “floor” is a minimum payout, conditional on thechosen geographical location (in which a market participant holds aninvestment unit) being “hit” (i.e. suffers a predefined amount or typeof contact with a storm).

In one example, the floor is the same fixed dollar value for allfinancial investment units in a given county (or other geographicalregion), and for all counties (all such regions). In one example, it iscomputed in the following way: One parameter in the pricing algorithm isprovided as the “par” value. Prices are computed as the product of theprobability (as assessed at any given time for the county or region inquestion) multiplied by the par value (and also multiplied by atime-value-of-money escalator). The par value is called “par” in thisexample, because, if the market is working smoothly, the payout a marketparticipant might expect is at or near the par level.

In instances where there is very strong buying activity, the actualpayout may fall below the par level. If it falls far enough below, thefloor is triggered. The floor, in one example, is a fixed percentage(specific value to be determined as a percentage of the par. For thefollowing example: it is assumed that a probability of the selectedcounty (or region) being hit, as assessed at the time of purchase, is5%, and that par value has been set at $1000. Neglecting thetime-value-of-money escalator, $50 is paid for one financial investmentunit. If the market works smoothly, the eventual payout, should theselected county be first hit, will be in the neighborhood of $1000. Butif market circumstances (e.g., very strong buying interest just beforelandfall) pushes the actual payout low enough, an expectation is, in theexample, given that a payout of least $800, will be received if thefloor has been set at 80%.

A mechanism is needed to honor the floor. One possibility is that, if anew purchase would drive the current indicated payout (total in anassumed pari-mutuel pool divided by number of financial investment unitsfor this county or region) below the floor level, the price for that newpurchase suddenly spikes to the floor level. In most cases this willdissuade the would-be purchaser from buying in a primary market, andmotivate that person to seek a better price in a secondary market, ifone is made available.

The present invention also contemplates considerations pertaining topayout, that address the timing of the payout, or conditions precedentto a settlement of the financial activity.

If desired, the payout can employ a sliding scale, based on any numberof factors that may be in play for a given financial activity.

Modularity

In one instance, one or more systems, one or more methods, and/or one ormore devices for carrying out the financial activity are provided. Anumber of important issues are addressed by the databases and/orprogram. In one instance, it is a generally preferred that these issuesbe addressed as much as possible, on a modular basis. In this manner, asystem administrator is able to quickly and easily tailor the financialactivity to meet a number of particular needs, and can modify thefinancial activity on an ongoing basis, if necessary. A briefdescription of some of the “modular” issues will now be given.

1. Definition of an external objective independent agency which monitorsa natural peril event, measures, observes, or otherwise obtains andrecords data concerning a natural peril event, as well as drawingconclusions and making analytical determinations concerning a naturalperil event. In one instance, it is generally preferred that theexternal objective independent agency be independent of theparticipant's financial activity, and in another instance be readilyobservable by the public, or at least the participants. For example, theexternal objective independent agency can comprise a unit of the UnitedStates government which routinely makes public announcements and whichis subject to Freedom of Information inquiries from members of thepublic.

2. Definition of an event eligible for payout. For example, relating tohurricane natural peril events, it is generally preferred in oneinstance that the event be “officially” declared a “hurricane” asdefined by the National Hurricane Center. However, in other instances,other recognized pre-hurricane stages can be treated by the financialactivity, with or without weighting the points upon which payout isbased. In one instance, payout for the financial activity can be basedupon an occurrence of a natural peril event or a termination of anatural peril event.

3. Definition of participant eligibility needed to be permitted toengage in the financial activity. Included, for example, is the level ofskill of the participant (needed, to qualify to participate in afinancial activity structured as a game of skill), or the propertyrights of participant (needed, for example, to qualify to participate ina financial activity structured as a vehicle for recouping losses toproperty rights caused by a natural peril event). It may be desirable,in certain instances to have an outside party handle these types ofactivities. For example there are a number of known enterprises thatassess the financial responsibility of individuals and businesses. Thisactivity may or may not be combined with an outside party that handlescash transfers and related matters.

4. Definition of a “season” for the financial activity. The financialactivity season can, for example, coincide with a particular timeinterval such as a “hurricane season” as defined by the NationalHurricane Center. In another instance, the financial activity season canbe chosen to lie outside of a recognized or customary time period suchas the National Hurricane Center “hurricane season” and that this ispreferred for hurricane natural peril events.

5. Number and length of financial activity seasons in a given year. Inone instance, there can be but one financial activity season. In oneinstance, the financial activity season can begin at the beginning of acalendar year. In another instance, the financial activity season canbegin at any time during a calendar year. In one instance, the length ofa financial activity season can be a predefined number of natural perilevents. In another instance, a financial activity season can be definedto comprise a predetermined number of natural peril events, which iseither concluded or is followed by a subsequent financial activityseason upon the occurrence of those predetermined number of naturalperil events.

6. Defining the types of natural peril events and activities upon whichpayouts are based. For example, for hurricane events, recognizedactivities can include coastal strikes, inland strikes and near-shorehurricanes which do not make landfall (such as hurricanes which comewithin one quarter mile of eligible coastal shore). Other definitions of“sub-characteristics can be made for other types of natural perilevents, other than hurricanes.

7. Defining areas or regions eligible for inclusion in the financialactivity. In one instance, only terrestrial areas or regions may bedeclared eligible for inclusion in the financial activity. In anotherinstance, the terrestrial areas or regions eligible for inclusion in thefinancial activity are geographically defined according to convenientdelineations, such as established political boundaries. In a furtherinstance, portions of geographic regions can be declared ineligible forinclusion (for example, some of the many island areas of the EasternSeaboard of the United States can be declared ineligible for inclusion,because of small size, few or no inhabitants, or for other reasons whichare or are not stated).

8. Defining the areas stricken by a natural peril event. In oneinstance, the stricken areas can be defined according to externalobjective independent agencies such as the National Hurricane Center. Inone example, stricken areas eligible for the financial activity includethose areas as defined by the National Hurricane Center “best-track” orother, interim reports which are typically published either during orshortly after the conclusion of a hurricane event. In one instance, thesize or width of the National Hurricane Center “best track” (preferably,of the center of the eye of the hurricane) can be infinitely thin, or itcan be of a predetermined width. In one instance, stricken areaseligible for the financial activity can be calculated by connectingpoints given in the National Hurricane Center table data of ahurricane's “best-track” or other table with either a straight line, ora curved line preferably defined by a predetermined curve-fittingmethod.

9. Defining the nature of the natural peril event to be eligible for thefinancial activity. For example, events officially determined to bewell-defined “hurricanes” by the National Hurricane Center can bedeclared by the rules of operation as the only eligible natural perilevent recognized by the financial activity. In another instance, thefinancial activity can treat “hurricanes” defined by the NationalHurricane Center according to their storm intensity as defined by theNational Hurricane Center. For example, only a hurricane defined asreaching category three severity by the National Hurricane Center can bedeclared eligible for the financial activity. In one instance, payoutscan be based upon hurricane strikes, weighted according to their stormintensity as defined by the National Hurricane Center. For example,distributions based upon a hurricane's “best track” can pay outdifferent amounts for different qualifying participants, depending uponthe severity of the hurricane at the time and/or point of contact withthe hurricane, or other primary, secondary, tertiary or other criteria.

In one instance, observed information from an independent externalsource regarding the land track of a tropical weather event may not becontinuously reported. For example, the use of a “best track” or othertable inherently assumes discrete points of data spread out over a timeinterval. Questions can arise when the reported data does not correspondto boundaries of geographical areas defined by the financial activity.Various treatments can be given. For example, an average value can beestablished between two adjacent data points (e.g. two adjacent pointsof a “best track” or other table) and this average value can be used todetermine the value of the natural peril event as it passed through agiven geographical area. In another treatment, if a data point (e.g. apoint on the “best track” or other table) occurs within a geographicalarea of financial activity, the value attributed to the data point canbe used for all investments made within the geographical area predictedby a participant. Other treatments are also possible.

10. Determining the amount of payout for those participants eligible toreceive payouts, as well as the conditions that must be present for apayout or other settlement to occur. Several instances of payouts variedaccording to a number of different factors and considerations are givenherein. These variations can be accounted for in a number of differentways including, for example, a simple linear weighting or a more complexalgorithm, formula, index or table, based upon historical events, orobserved natural peril events, for example. In another instance,variations in payout between different participants can be based uponone or more related or independent factors, as may be desired. In oneinstance, determining the amount of payout for qualifying participantscan be based upon primary, secondary and if desired, tertiary and othercriteria. For example, for tropical weather events, primary criteria canbe chosen to be the “locus” of landfall of a tropical weather event. Ifdesired, the land track of a tropical weather event can be treated asanother primary criterion (especially where an equal weighting amongprimary criteria is assumed) or can be treated as a secondary criterion(especially where unequal, preferably a lesser, weighting is assigned,relative to the primary criteria). In another instance, other secondaryor lower level criteria can be chosen, such as residence time in a givengeographical area, or wind speed or range of wind speed associated witha tropical weather event, preferably while the tropical weather event isresident in the geographical area predicted by the participant. As afurther possibility, multiple criteria can be established in tertiary orother additional levels (preferably assuming unequal weighting among thelevels of the criteria).

Other examples of variability factors are discussed herein.

Derivative Trading Financial Activity Model

As mentioned above, financial activities may, in one instance, bemodeled to include or resemble financial trading of derivativesecurities interests (e.g. options), such as those monitored by theCommodity Futures Trading Commission (an independent agency of theUnited States government), the New York Stock Exchange, the ChicagoMercantile Exchange, the Iowa Electronic Market, and others. Thesefinancial activities may include, for example, futures contracts,options contracts, options on futures contracts and other forms ofderivative products

Generally speaking, compared to other types of financial activitiesconsidered herein, activities under the “derivative trading type”financial model may, in one instance, incorporate price controls drivenmore by market conditions and less by direct control via the rules,principles of operation and other structures of the financial activitybeing undertaken. If desired, the financial activity may be entirelymarket driven.

According to one example of this financial activity model, and assuminga hurricane or tropical weather type of natural peril event, initiallyall geographical areas (e.g. counties) in play are available forindividual investments at the beginning of the declared financialactivity season at some predefined minimum investment amount (i.e.purchase price). A first example of a derivative trading financialexample is referred to herein as the FIRST LANDFALL OPTIONS, or FLO. Asmentioned herein, the principles set out in the following and otherexamples, may be readily applied to other types of natural peril events.For instance, the following first landfall options could be readilyrecast as a first tornado or earthquake strike options based ongeographically defined areas of these types of natural peril events.

First Landfall Options, or FLO

1. Background. On average for the last 130 years, two hurricanes makelandfall in the U.S. each year. The activity will assume there are 78individual counties, parishes or other land units on the Atlantic coastof the U.S. plus five groups of Mid-Atlantic and New England counties.For simplicity, we will call each of these five groups a “county.” Anyof these 83 “counties” could be the first place a hurricane makeslandfall in the U.S. (or the place another natural peril event occurs).Or none of these counties could be hit by a hurricane. It will bereadily appreciated that the FLO financial activity can be conducted forother numbers of geographical areas, and for other types of naturalperil events where a loss or other significant event occurs, arisingfrom natural forces, i.e. other than man-made, intentional events.

2. First Landfall Options (FLOs) allow parties to hedge or speculate onwhether their selected county will be the first county where a hurricanemakes landfall in the U.S. FLOs are commodity options—the commoditybeing defined in exchange rules to be where a hurricane will makelandfall first. FLOs will be traded on an exchange, a designatedcontract market under the Commodity Exchange Act. Under exchange rulesfor FLOs, a market participant selects one of 84 counties (including the“no hurricane makes landfall” county, called the “null” county) whichthe market participant fears (or believes, or both) will be the U.S.county where a hurricane will first make landfall. That marketparticipant is “long” the county selected and “short” all the othercounties. The market participant pays a premium reflecting this combined“call” on the county selected and “put” on all the other counties. Themarket participant can lose only the amount of the paid premium. If thehurricane makes landfall first in the county selected, the FLO holdersfor that county receive a pro-rata share of the combined proceeds frompremia received and deposited with the exchange for all FLOs purchasedfor all counties in that option series. In other words, all FLOpurchases fund the pay-out to the holders of FLOs for the county wherethe hurricane first makes landfall. As indicated herein, payouts can beadjusted to offer an expected minimum payout, especially for thosegeographical areas in play that suffer verifiable damage.

3. FLO Series. Three options series of FLOs will be offered initially.Based on the historical data, three FLO option series would seem to beadequate because in 90% of the years three hurricanes or less makelandfall in the U.S. Each FLO options series would be comprised ofoptions on each of the 83 counties plus the null county.

4. FLO Example. In a first instance, there is only one county where ahurricane makes land fall “first.” Therefore, a FLO buyer for MonroeCounty is “long” Monroe County and “short” all other 83 counties. If thehurricane makes landfall at Monroe County first, the holders of FLOs onMonroe County receive a return on their option. If the hurricane makeslandfall first in any other county, then the holders of FLOs on MonroeCounty receive nothing. Their option expires and can not be exercised.No holder of a FLO can ever lose more than the purchase price (thepremium) for the FLO. If desired, in another example, a natural perilevent can strike two adjacent geographical areas simultaneously, if thenatural peril event is broad enough to do so.

5. FLO Trading Information Market Participants Would Always See. Througha link on the exchange web-site, all market participants will be able toview FLO market data for each of the 84 counties. First, for eachcounty, the market participant would see a percentage number reflectingthe likelihood, based on historical data analyzed algorithmically, thata particular county would be the first county, out of the 84 possiblecounties, where a hurricane would make landfall first in the U.S. orthat no landfall would occur. Second, based on that likelihood for eachcounty, each market participant would see what the FLO for each countythen costs—the premium for the combined call-put option. Third, eachmarket participant would see updated in real-time the number of marketparticipants who have bought a FLO for any county and the proceedsreceived by the exchange to date for all FLOs for all counties. Fourth,on a real-time basis market participants would always be able to see thecurrent value of the FLO for each county. That is, market participantswould know what a FLO holder for Monroe County would receive if noadditional FLOs were bought by market participants and a hurricane madelandfall first in Monroe County. It is anticipated that exchange ruleswill set out the length of the trading day to be 12 hours, from 8 am to8 pm eastern time. Market participants would be able to access theexchange-web site at any time (maintenance may require a short hiatus atsome time during the night) for informational purposes but would be ableto execute FLO purchases only during the 12 hour trading day period. Ifdesired, activities can be conducted for other time durations, such asextending trading to 15 hours, from 8 am to 11 pm, for example.

6. FLO Market Value Variables. The variables that would affect the FLO'smarket value for any county at any time are fully transparent andavailable to all market participants: a) number of FLO purchasers in theselected county; b) number of FLO purchasers in all other counties; andc) the monetary amount paid for all FLOs to date. This information isupdated dynamically on the web-site. No market participant should havean information advantage over any other market participant.

7. FLO Primary Trading: Pre-Tropical Storm Period. Until the firsttropical storm is reported in the Atlantic Ocean, usually July, no datais available on hurricane landfall probability other than historicaldata. Until that first tropical storm is reported, the exchange web-sitewill provide market participants with the price for each FLO county (theFLO premium), including the “null” county, based on an algorithm derivedfrom the historical likelihood that a hurricane will make landfall firstin a particular county. The exchange expects to discount these premiafor the earlier calendar months and then increase the premia as the timefor the expected first reported tropical storm approaches. It would becheaper to purchase a FLO in January, for example, than in April. AssumeMonroe County's historic risk premium is $100, the exchange could decideto reduce that premium for market participants purchasing in January to$50. Again, all market participants would be able to buy each FLO for aparticular county at the same price and all would receive the sameamount of advance notice of any discounts granted by the exchange. Oneexception to this rule might be for hedgers. The exchange could reducethe FLO premium just for hedgers—those who represent and show that theyhave property or business operations in the FLO county selected (or incontiguous counties). Other arrangements can be made for the discountingof the premia. These FLO premium prices would be disclosed to everypotential buyer on the exchange's web-site. Buyers also can see on theweb-site how the market forces are driving the potential strike pricefor each FLO—or what each FLO holder would receive if the countyselected was, at that point in time, the first county where thehurricane made landfall. This information is updated dynamically on theweb-site. No secondary trading will be permitted in FLOs during thisphase.

8. FLO Primary and Secondary Trading: Post-Tropical Storm. Once atropical storm is reported by the National Hurricane Center, theexchange will offer both primary and secondary trading facilities forthe FLOs that are part of the first options series. (When the second andthird tropical storms are reported, the exchange will offer primary andsecondary trading facilities for the FLOs in the second and thirdoptions series, respectively). In primary trading, the exchange willcontinue to publish the prices at which FLOs may be purchased at apremium priced to reflect the historic algorithmic likelihood of thefirst landfall plus the data analyzed from the actual storm trackingsoftware. These primary trading prices will be eligible to be updated atleast four times a day in accordance with the four daily storm trackingreports issued by the National Hurricane Center. In short, the primarytrading price will be an algorithmically-determined combination ofhistory and environment updated dynamically. Secondary trading will bebased solely on offers to sell or offers to buy FLOs received frommarket participants through an electronic auction market trading system.Offers to sell FLOs would have to be made by those that already ownedFLOs, no naked short selling will be allowed. The exchange will providefor clearing of all secondary trades, including the settlement transferof any FLO from the seller to the buyer.

9. Landfall. Exchange rules will establish the criteria, based oncredible third-party observations, for determining when and where ahurricane makes landfall first or a geographical area suffers damagecaused by other types of natural peril events. They are expected to bebased on the publicly-available NHC estimates of the position of thestorm center through time, and on geographic boundaries for the countiesprovided by Census Bureau data bases. Once the hurricane hits, thatevent is over. At some point before the hurricane makes landfall, theexchange rules will have to specify when FLO trading is suspended as thehurricane nears. The exchange does not want market participants incertain regions to be disadvantaged by a storm's imminent arrival.Exchange rules, for example, could specify that primary trading endsonce a hurricane watch is issued for one of the 83 U.S. counties andsecondary trading ends once a hurricane warning is issued for one of the83 U.S. counties. As mentioned elsewhere, public safety and the need tocoordinate various government agencies may require adjustments to theactivities described herein, without departing from the spirit and scopeof the invention.

10. Bounce-back Effect. Sometimes a hurricane will make landfall andthen head back out to sea before returning to make landfall a secondtime. For purposes of FLO trading, this occurrence can, in one instance,be considered to be two hurricanes, each with a FLO and resultingpayout. Exchange rules will specify the criteria for how far out to seaa hurricane must go before it is considered to be a “new” hurricane forpurposes of the FLO product.

11. Null County. Under exchange rules, payouts to holders of the nullcounty FLO occur only at the conclusion of “hurricane season,” generallyconsidered to be December 1. If no hurricane makes landfall in the U.S.,for example, the null county holders for all three FLO series willreceive a pay out from their respective options series premia. If onehurricane made landfall, then the holders of null county FLOs for FLOseries 2 and 3 would receive payouts. Timing of payouts would be set byexchange rules.

12. Other issues. Adding new options series during storm season couldreceive different treatments. For example, a new FLO could be listedwhenever a third storm appears, and a new FLO could be listed when afourth storm appears. Although these FLOs could be funded in a number ofdifferent ways, build up from the early winter sales will be avoidedbecause there will preferably be no winter sales in these FLOs; and theywouldn't be authorized until storm season, in July or August as thelikely earliest time. Either a funding or seed funding source could beprovided or market forces can be relied upon exclusively. In oneexample, it is contemplated that FLOs can be purchased throughintermediary FCMs only, or, alternatively, FLOs can be purchased eitherdirectly by consumers or through the services of an FCM. Marketparticipants can have access either through an exchange web-site orthrough an authorized intermediary (FCM) to execute the purchase of thecommodity option. The FCM can then collect the customer's money and willforward the funds to the exchange or its custodian of the funds.

The concept of a first landfall can be regarded as addressing thecoastal areas that are exposed to hurricane damage. Of course, damageoften continues as the natural peril event travels inland, and provisioncan be made for inland geographical areas as well. Receipts collectedcan be disbursed to a greater number of geographical areas, based on aprior contract or other rules establishing a condition forqualification, as where a natural peril event impacts inlandgeographical areas. Such impact could be qualified based upon anofficial track, or a minimum amount of damage or damage claims, forexample. Such damage could also be caused by a tornado, an earthquake,or other type of natural peril event.

Trading Utilizing a Severity or Property Damage Scale

A second example of a derivative trading financial example alsocontemplates financial activity concerning property owners' exposure orrisk of exposure to damage related to hurricanes and other naturallyoccurring events. It has long been recognized that a hurricane's ortornado's potential to inflict damage to property can be estimated fromvectored wind speeds, such as translational and rotational wind speeds,and other observed characteristics such as the storm's radius or othersize-indicating data. According to the present invention, a scale orindex of measurement is derived from a events of observed factsconcerning hurricane characteristics. The observed facts are preferablyprovided by a responsible third party, such as a government agency orweather information specialist service or a damage prediction service,for example. Examples of observed facts include temperature, humidity,wind speed, and wind area relating to a storm. Observed facts alsoinclude storm intensity forecasts provided by the National HurricaneCenter, for example.

Values on the scale provide an indication or measurement of the risk ofproperty damage as a result of the exposure to an historical orforecasted hurricane (or other like natural peril event). In oneinstance, the values are calculated or computed numbers and the scale ofvalues may be in the form of an index, table or other data construct.The indication or measurement of the risk of property damage can, forexample, relate solely to the likelihood of landfall, or could relate tothe prospect of landfall with or without consideration of stormintensity and with our without consideration of property values exposedto the storm. In another instance, indication of damage is based uponactual or estimated insurance claims. Claims for certain types of damage(hurricane or flood or earthquake) could be excluded, if desired.

In one variation of financial activity according to principles of thepresent invention, derivative products such as futures (forwardcontracts), and options (option contracts) are traded multilaterally(one or many trading with many) or bilaterally via an exchange or otherdealer or privately, i.e. directly, between a buyer and seller. As afurther alternative, a manager of a financial activity may allow privatecontracts and other dealings to be later cleared through an exchange'sclearing system. Preferably, the various contracts are settled against ascale, expressed, for example, as an index, a table, or other dataconstruct, that is calculated with reference to observed facts relatingto natural peril events, such as those mentioned elsewhere, herein. Thescale could relate, for example, to the likelihood of first landfall, orthe potential of the naturally occurring event to cause damage toproperty exposed to the naturally occurring event. The scale could beemployed as an index, used in the manner of conventional futurestrading, with financial activities modeled after conventional futurestrading (i.e. forward contracts and options contracts) in indexes. Theindexes could, for example, be allowed to vary in value as the naturalperil event matures, with trading being settled according to indexvalues on separate days

The scale can be expressed in terms of continuous or discontinuousnumerical series. Virtually any basis for the scale(s) can be used. Forexample, scales or indexes measuring expected property damage can bebased on meteorological data such as velocity (e.g. high wind speeds)and overall size such as radius data for storm (hurricane) winds. Suchdata can include, for example, a single radius of hurricane force winds,or arrays of hurricane force winds in a more complex analysis. Otherbases for the scales could chosen from data relevant to insuranceinterests, such as property damage claims as well as establishedinsurance and reinsurance indicators of damage, damage risk as well asclaims presented for settlement according to accepted insurancepractices. If desired, the financial activity can employ more than onescale. For example, different scales could be used at different stagesof a hurricane's progression, such as the storms development at sea,first landfall (usually, for a specified region). Multiple scales couldbe employed, for example, where a number of indexes are put in play forsuccessive hurricane landfalls in a given season. Each index could beseparate from the others, and allowed to fluctuate according to ongoingmarket valuations and activities. For example, the indexes couldfluctuate in value according to market performance of the financialactivity, or alternatively, according to technical information such aschanging forecasts by the NHC or other independent third party

The separate indexes could be settled separately, for example, shortlyafter the hurricane makes landfall. Different scales could also relateto the overall cumulative effect of natural peril events over a periodof time, such as a hurricane season, for one or more regions ofinterest. Further possibilities include scales relating to a largest ormost powerful or most sustained storm in a particular area, as definedby the activity. If desired, a cumulative long-term index based upon twoor more shorter term indexes, can be traded. Alternatively, a cumulativeindex can be based upon individual indexes for two or more geographicregions. If desired, indexes based upon permutations or combinations ofdifferent types of indexes can be used, including indexes for differentgeographic regions and indexes for different time durations.

Contracts for the futures and options on futures, and other financialactivity products are preferably created for defined geographicalregions exposed to hurricane and other naturally occurring events. Ifdesired, where hurricanes are the naturally occurring event of interest,the scale(s) employed could relate to the hurricane's first landfall, arange of geographical regions over which all hurricanes for a seasonmake landfall, or geographic regions suffering exposure to a minimumstorm force. First landfall could be on a geographicregion-by-geographic region basis, or on the basis of all definedgeographic regions taken together, or in multiple-region subdivisions orother defined manner. If desired, derivative products or other financialactivity could be defined for natural pre-hurricane events. For example,derivative products can be defined when a storm activity reaches atropical depression stage as determined by the NHC or other authorities.Further, such products can be defined for different geographical areasdefined by the activity, such as storms occurring in different regionsof the sea, such a more northerly Atlantic regions and more southerlygulf coast regions. Such activities could be tied to market interestsrelating to more southerly gulf coast exposures as compared to morenortherly Atlantic coast exposures. Trading for such products cancontinue, for example until landfall or until the storm expires at seawithout making landfall. As a further alternative, products related tonatural peril events originating in one geographical region can beexpired or converted into different products when the underlying naturalperil event leaves one geographical region and enters another.

In one example, the financial products including derivative contractscan be delivered or otherwise settled in a variety of ways. For example,they can be settled with reference to a final price determined accordingto a scale, or according to market activity or according to one or morealgorithms or any permutation or combination of these. Further,settlement can be made in the context of a pari-mutuel activity, or afixed settlement method, or a combination of these. If desired, thefinancial activity can allow, or regulate or facilitate secondarytrading, where financial products are traded between participants beforeor after settlement. In one example, futures and options on futuresbased on first landfall of a hurricane with respect to one or moredefined regions, are traded during a hurricane season, prior to firstlandfall. Market forces can control prices in this secondary trading, ifdesired, or prices can be regulated by the financial activity, in somemanner. Settlement is made after first landfall, either at a fixed priceor a price determined by the financial activity, for example, accordingto principles set forth herein.

In one variation of financial activity according to principles of thepresent invention, financial products such as futures contracts, optionscontracts and options on futures contracts, are cleared through afutures exchange. The contracts may be created for defined geographicalregions exposed to hurricanes and other naturally occurring activity,and are preferably settled against one or more embodiments of a scale ofmeasurement of the type described above, or herein, derived from aevents of observed facts concerning characteristics of natural perilevents, especially characteristics related to a potential of a naturallyoccurring event to inflict property damage. Values on the scale may beexpressed in the form of an index, a table, or other data construct asmay be desired. The contracts may set a lower limit on the amount ofdamage contemplated. The contracts may be limited to future potentialdamage exposure, or may be implemented for actual sustained damage,preferably damage estimates provided by a responsible external thirdparty, such as a government entity or insurance or reinsurance service.If desired, the scale may be based in whole or in part on informationprovided by such government entity or insurance or reinsurance service.

In general, contracts considered herein could be defined in terms ofactual or estimated future damage, with or without a set minimum amountof damage, or the likelihood that a defined amount of damage is reportedfor a particular storm, a range of dates or an entire season. Ifdesired, the contracts could be defined on a storm-by-storm basis, orcould be limited to the storm having the greatest impact in the chosencategory (damage caused, size of storm, strength of the storm, measuredin some predetermined manner, size of coastal area or land areaaffected). If desired, contracts could also include offshore propertiessuch docks, or harbors, or ships that are moored, tethered or otherwisepresent within a defined proximity to land.

If desired, multiple scales can be provided for each geographic region,or different time divisions, such as different date ranges, and could beprovided for different natural peril events, in which each firstlandfall of a season terminates the current part of the financialactivity, with a new, subsequent part being started. In each of thevariations herein, contracts could also be offered for a “null” event inwhich no landfall is reported for a given season or other defined timeperiod.

Sarasota County Example

As a further variation, one financial activity according to principlesof the present invention contemplates trading of contracts utilizing afutures index. As will be seen herein, the contracts are written for afirst landfall criteria, although different criteria based on othertypes of natural peril events could be employed, as well. This variationassumes interest in a particular geographical region, referred to hereinas Sarasota County. It is assumed in this variation, that, although thestorm is still some days away from occurring (e.g. away from landfall),that it is becoming more likely that the storm may be heading forSarasota County.

An index is provided as a basis for trading geographical regions, andfutures contracts are offered for trade. The Sarasota County Index risesas it becomes more likely Sarasota will be First Landfall (or otherwisesubjected to damage), and falls as it becomes less likely. The futurescontract on that Index are based on the proposition that, when the firststorm makes landfall, all futures contracts expire and buyers or sellersmust pay off based on what the last index price was before Landfall. Thevariation focuses on two participants, a first participant that thinksSarasota will be hit first, and a second participant that doesn't. Thefirst participant buys a Sarasota Index futures contract at $100 onMonday, and accordingly is long on Sarasota County The secondparticipant sells a Sarasota Index futures contract at $100 on Monday,and accordingly is short on Sarasota County. Both participants paymargins as required by exchange rules and by contracts with theparticipant's “clearing firms.” For discussion purposes, eachparticipant pays $5 in margin to their clearing firm.

By Thursday, it looks like Sarasota will be hit over the weekend. TheSarasota Index rises. The price of the Sarasota futures contract alsowill rise. It is assumed that, based on bids and offers from all marketparticipants, the price for the futures contract on Thursday is $125. Ifthe first participant decides to settle for this profit, the broker isinstructed to liquidate the first participant's future position throughan offsetting trade. The broker for the first participant then goes intothe market and sells a second Sarasota contract at $125 on behalf of thefirst participant. The resulting sell contract cancels out or offsetsthe first participant's buy contract. In the sale, the buyer is assumedto be a third participant. The first participant receives a profit of$25 (along with return of the margin paid).

On Friday, the storm turns sharply and heads towards Texas. The SarasotaIndex plummets. The price of the Sarasota future is assumed to drop to$10. Assuming the first participant wants to maintain a position onSarasota County, and the first participant's broker finds a participantwilling to sell at $10, the resulting buy order at $10 cancels the sellorder at $100 and leaves the first participant with a profit of $90.

Additional Considerations

In one example, once an investment is made for a particular geographicalarea, the next investment to be made for that same geographical area isset at a higher purchase price. For example, the rules of the financialactivity can provide that the second investment will undergo a flat ratepricing increase, such as $0.25 per financial investment unit. Ifdesired, pricing increases can be assigned in steps according to stepincreases in the volume (either dollar amount or number of financialinvestment units traded) of trading. If desired, other types ofincreases can be employed, including linear and nonlinear mathematicaltreatments of purchase price. The prices for subsequent investments in aparticular geographical area may either continue to increase or willplateau at a constant price until a set point minimum number offinancial investment units is reached. In this example, preferably, theset point is chosen to reflect a pool of money of substantial size,which would justify a substantial step in price increase. If desired,several steps of price increases can be employed and related to similaror different sized blocks of financial investment units. If, forexample, a particular geographical area suffers a lull in trading, thepurchase price can be reduced, based on the time value since the lasttrading activity. Once activity resumes for a particular geographicalarea, price increases can go into effect. Each geographical area willhave different initial prices and could have different step sizes orblocks, as financial investment units are traded, if desired. Thus, inthis example, financial investment unit price varies according to marketactivity (e.g. a stepwise or a smoothly varying increase as tradingactivity increases). Optionally, in this example financial investmentunit price can also vary according to time factors, such as factorscentered around a falloff (or optionally a rise) in trading activity.

It is generally preferred that pricing follows a number of principles.For example, it is generally preferred that trading begins with a setminimum price which could be different for each geographical area. Inone instance, it is generally preferred that the minimum price dependson market activity. In a second instance, it depends on theclimatological probability, (as currently estimated), of the particulargeographical area being hit, and, as trading progresses, how manyfinancial investment units have been sold for a particular geographicalarea, and also the total amount of money in the pot. If desired, each ofthese principles can be applied in different amounts, (e.g. according todifferent increments, different rates or other mathematical treatment).It is generally preferred that the minimum price increases as theprobability for a hit in the geographical area increases, and theminimum price should also go up as the total dollars in the pool ofmoney goes up. In one instance, it is generally preferred that theminimum price goes down as the number of financial investment unitspotentially splitting the pool of money (i.e. for a particulargeographic area) goes up. Other considerations regarding pricing arementioned herein.

Auction-Based Financial Activities

As another example, in a maturing market, the ongoing financial activitycan be alternated (less preferably, replaced) with an “auction” form offinancial activity. In one instance, the auction form of financialactivity, once initiated, is scheduled to occur at different intervals.For example, multiple auctions would preferably occur periodicallythroughout the season, in one instance, with the time spacing betweenauctions being sparser (e.g. weekly or monthly) early in the process,and more frequent (e.g. multiple auctions per day) when tropicalcyclones are in existence and especially when hurricanes are threateningimminently. this example, the event price for an auction is preferablymade proportional to the probability that a particular geographic areawill be hit, multiplied by the funds available, and that product dividedby the number of financial investment units outstanding for thatparticular geographical area. If desired, the proportionality constantapplied could be unity or some number smaller or greater than one.

Variation 1: Assuming a first auction has concluded at a time inJanuary, before the conventional hurricane or other natural peril eventseason, the “stage 1” probability, calculated as set forth herein, is0.02. Assuming the previous financial activity sold 5000 financialinvestment units for the geographical area of interest, and thatcollectively, all the auctions took in $25 million overall. The minimumunit price would then be (0.02)×($25 million)/5000=$100, and therefore,nobody could bid less than a $100 minimum price. If there were moretakers than financial investment units, some or all of the bidders at$100 would be out of luck.

Variation 2: Assuming a time in July, when there is a tropical storm orother natural peril event in existence, in a location that is favorablefor hitting the geographical area (e.g. county of interest. The “stage2” probability for that area is calculated as set forth herein to be0.10. There are now 100,000 financial investment units that have beenbought for the geographical area of interest, and the total pool ofmoney is $2 billion. Minimum bid price would be (0.10)×($2billion)/100,000=$2000.

Variation 3: That tropical storm or other natural peril eventcontemplated in variation 2 has dissipated and now poses no threat tothe geographical area of interest. Also, there are currently no otherstorms or other natural peril events that are threatening, and theprobability drops back to 0.02. There's now $2.1 billion in the pot, and105,000 financial investment units have been bought for the geographicalarea of interest. The minimum bid price has gone down because theprobability has gone down: (0.02)×($2.1 billion)/105,000=$400.

In each of the variations above, there would preferably be separateauctions for each geographical area in play (with one or more auctionsfor each geographical area), with the degree of market participantinterest determining whether and/or how much the price would rise abovethe levels indicated. Also, it is generally preferred that the number ofunits on offer at any one time would be limited to a fixed number, itbeing expected that, if the total offer is unlimited, there would be noincentive to bid higher than the price.

If desired, special treatment could be given later in a financialactivity season when it becomes clear that certain geographical areasare unlikely to ever be perceived as generating substantial marketparticipant interest (e.g. inland geographical areas that historicallyhave not, or only very rarely, been hit.

ADDITIONAL EXAMPLES

In another example, trading contracts corresponding to differentgeographical sections, have contract prices set by market forces, thatis, by the participants, rising and falling based on their degree ofconfidence of where landfall will occur. The value of these contractswill rise and fall based on market acceptance of a forecasted stormoccurrence.

In a further example, derivatives trading is based entirely on“market-based” pricing. Here, “market-based” pricing refers to pricingthat is based on recent or cumulative market activity. If desired, themarket-based pricing may or may not be driven by algorithms, or onlypartially driven by algorithms, as may be desired.

In another example, futures contracts, options contracts, options onfutures contracts and other forms of derivative products may pay outupon occurrence of a specified condition (e.g. first landfall of ahurricane), preferably on a non-pari-mutuel basis, are offered for saleto prospective purchasers. Most of the contracts represent differentcoastal areas subject to first strike by a hurricane, typically,portions of the Atlantic and the Gulf seacoast. If desired, contractsfor non-landfall conditions can be added to the offering, such as astorm at sea entering a defined zone. Prices of the futures contractswill vary during a storm season, with prices for particular contractsrising according to market activity as a storm approaches the territory(or other condition) defined in the futures contract.

As can be seen from the above, the present invention contemplates anumber of features concerning derivative products, including financialactivities directed to catastrophic events, especially non-human created(e.g. “natural”) events (landfall for a hurricane, location for aearthquake or tornado, etc.), a prediction of the location and/or thepotential for disaster of the future event. Settlement is determinedagainst information provided by an independent, responsible third party(that provides, for example, a determination of landfall, location ordamage amount). Settlement may be of a pari-mutuel type, market-driventype, or a mixture of market forces and pari-mutuel types. The financialactivities may contemplate scales or indexes concerning the subjectmatter involved, such as a third party estimate of the degree of damagesustained (such as the amount of insurance claims asserted or an indexbased upon such data), or the severity of the event (such as wind speedsor other damage potential of a hurricane). Derivative activities may beconducted between pairs of participants, or between unequal numbers ofparticipants or between one or more participants and a financialinstitution. Derivative activities may involve algorithms, such asalgorithms for setting pricing of some portion or all of an activity, ormay react solely r partially to supply and demand and other marketforces. The above features may be entirely or partially aggregated invirtually any permutation or combination, or may be left out altogetheror may be replaced by other features contemplated herein.

In other aspects, the present invention contemplates futures contracts,options contracts, options on futures contracts and other forms ofderivative products, traded multilaterally or bilaterally, where thecontract's or product's value increases or decreases based upon ameasure or index of estimated or actual: property damage or likelihoodof property damage, whether caused by a weather event or other form ofnatural peril, in a specified region or geographic locations. Thecontract's or product's value may increase or decrease based upon ameasure or index concerning where a weather or other natural peril eventwill occur (e.g. make landfall first) in a region or geographical area.The contract's or product's value may also increase or decrease basedupon what the seasonal impact of weather or other natural peril eventswill be in a specified region or geographic area and may also be basedupon what the maximum or largest weather or other natural peril eventwill be in a specified region or geographical area. Again, permutationsand combinations of these financial activities are possible.

“Hurricane Pools” Financial Activity I. Summary

The following description is directed to examples of financialactivities according to principles of the present invention that arereferred to as “Hurricane Pools” or “Storm Pools.” The following is oneexample of financial activity contemplated by the present invention. Asmentioned, different types of financial activity models may be employed.The following example is given in terms of a financial activity model ofthe type comprising a game of skill, although many of the principles setforth herein are applicable to other financial activity models, as well.The financial activity contemplated herein is generally referred to as“Hurricane Pools”, emphasizing the investment nature of the financialactivity as a hedge against unforeseen loss. In the example given, theHurricane Pools are games of skill that focus on a particular type ofnatural peril event, namely hurricanes making landfall in the UnitedStates. That is, in this example, only tropical cyclones having astrength meeting the minimum criteria to be termed “hurricanes” areconsidered. Those skilled in the art will readily appreciate that othertypes of natural peril events can be treated as well.

It is recognized that a tropical cyclone originates at sea, and grows inintensity over time, before making landfall. It is possible that theintensity of the tropical cyclone may rise and fall. The criteria chosenhere is that the tropical cyclone has a minimum category one hurricaneintensity at the time of landfall. The Hurricane Pools are structured toallow market participants to use them in a way that can augmenthurricane insurance, while simultaneously providing income toparticipating states to help defray costs associated with disastermanagement. Homeowners and business insurance policies typically containdeductible provisions ranging from 2% to 15% of a home's value. Inaddition, these same policies do not provide any coverage for theoutside areas of a home or business, such as landscaping, outsidelighting, docks, fencing and the like. Often, property owners do nothave sufficient flood insurance and have other omissions or insufficientcoverage which result in catastrophic financial losses in even thelowest rated hurricanes. Also, losses are suffered when rates are lostand also, where temporary housing is needed.

Because financial activities can be carried out according to differentfinancial models. The Hurricane Pools, for example can be distinguishedfrom insurance instruments, with payouts for qualifying investments notbeing tied to actual property losses, and thus being dispensed morequickly. Payouts here do not involve inspection by adjusters, andtherefore can be made much more promptly—(e.g. within a few weeks). Thispromptness and flexibility can be achieved because the Hurricane Poolsoperate in a way that emphasis is placed on payouts that primarilydepend upon apportioning Hurricane Pools that have been invested into aparticular Hurricane Pool, and on the amounts and timing of HurricanePool entries for counties that experience a hurricane strike.

As mentioned above, financial activities may be constructed aroundmodels that cover the natural peril event activity either on an event byevent basis, or on a “seasonal” basis for events occurring during apredefined span of time. In the example given above, choice was made tooperate on the “seasonal” basis. Accordingly, the number of HurricanePools in which market participants may participate can vary from year toyear, depending on the number of officially declared eligible events. Inthis instance, the Hurricane Pools may be regarded as different eventsoccurring in a season. Initially, two or three Hurricane Pools may beopened to investment, beginning on 1 January. Each of these initialHurricane Pools relate to one of the first two or three tropicalcyclones passing over a portion of the U.S. with at leasthurricane-force winds during the upcoming calendar year, as determined,in one instance, from the tropical cyclone Advisories issued by theNational Hurricane Center (NHC). The overwhelming majority of theseevents occur during the span of time, popularly referred to as the“hurricane season” (1 June through 30 November). In active hurricaneseasons, additional Hurricane Pools may be opened as the hurricaneseason progresses.

Each investment in a Hurricane Pool is preferably made in the form offinancial investment units or the like, purchased for one or more of thegeographical regions, such as counties (or county equivalents, forexample Louisiana parishes) that are plausible hurricane targets. Whenthese financial investment units have been purchased for counties thatlater receive a hurricane strike, they qualify their owners to receivepayouts from that Hurricane Pool. All of the investments in a givenHurricane Pool, less items which may be defined in a given instance(e.g. portions designated for participating state governments and feesfor Hurricane Pool management), are paid to market participants in thequalifying county or counties. The formula determining these payoutsaccounts both for the chances of a hurricane striking the qualifyingcounty(s), as assessed at the time a Hurricane Pool investment is made,and a reward for earlier investments into that Hurricane Pool.

II. Structure of Hurricane Pool Investments A. Hurricane Pool FinancialInvestment Units

Entries in the Hurricane Pools are made for individual counties, in theform of “financial investment units” in one of the specific HurricanePools available for investment. The first Hurricane Pool relates to thefirst tropical cyclone to make landfall as a hurricane over the U.S.,including Puerto Rico and the U.S. Virgin Islands; the second HurricanePool relates to the second hurricane striking the same area; and so on.For example, suppose the first U.S. hurricane landfall in a hypotheticalyear is at Galveston County, Tex., and the second is at Miami-DadeCounty, Florida. Financial investment units purchased in Hurricane Pool#1 for Galveston would qualify their owners for a portion in all of themoney invested in that Hurricane Pool, but market participants inHurricane Pool #1 for Miami-Dade would receive nothing from thatHurricane Pool. On the other hand, market participants in Hurricane Pool#2 for Miami-Dade would be entitled to a portion of all of the moneyinvested in that Hurricane Pool, whereas Galveston market participantsin Hurricane Pool #2 would receive nothing from that Hurricane Pool.

The primary means of making Hurricane Pools investments will, in oneexample, be by credit card, through a Hurricane Pools website. Oneexample of a web site is given in FIGS. 13-18, which shows a web siteimplementing a Hurricane Pool financial activity. FIG. 13 shows a website screen which serves either as a welcome page or one of the firstpages that a participant will encounter upon acquiring the web site.Included in the screen depicted in FIG. 13 is an indication 600 of thecurrent open Hurricane Pools and a brief summary 602 of current tropicalcyclone activity.

In one instance, in addition to providing web site access, individualswho do not have internet access will also be able to participate in theHurricane Pools by using touch screen displays and other examples ofgraphical user interfaces, located at convenience stores, gas stationsand the like. Individuals will make selections by touching aninteractive screen, for example, and pay for their investment by swipinga credit card or providing a cash payment to the retail establishment.Preferably, the display will automatically generate a printed receipt(including identification number) for both credit card and cashpurchases. A social security number and perhaps a biometric device suchas a fingerprint scan may be required to participate in the HurricanePool.

FIGS. 16-18 show financial investment unit purchases for the Storm Poolweb site implementation of a Hurricane Pool. In FIGS. 16 a and 16 b-16 ctwo screens are shown for purchasing financial investment units and inFIG. 17 a confirmation is given for financial investment unitspurchased. In FIG. 18, a summary or “portfolio” of all transactions fora participant is shown.

Once an investment in a Hurricane Pool is made, the investmentpreferably cannot be reversed as these would affect the value of thefinancial investment units purchased by others. In one instance, aninvestment is not considered to have been accepted until the marketparticipant's credit card company credits that investment in theHurricane Pool. If the credit card company later reverses that paymentto the Hurricane Pool, the value of the financial investment unitspurchased in the Hurricane Pool will be preferably set to zero.

B. Financial Investment Unit Prices

The price of a Hurricane Pool financial investment unit for a particularcounty is, in one instance, determined by a mathematical formulainvolving both the probability of that county being hit, and pricediscounts for early investments. Therefore, financial investment unitprices in Hurricane Pools will be different at different times anddifferent for different counties at a particular time.

The price incentives for early investment may be substantial, and aredesigned to encourage investments before any tropical events are inexistence, and indeed well before the beginning of hurricane season. Itis anticipated that much of the early investment activity will come frommarket participants who may want to use the Hurricane Pools tosupplement conventional insurance, or from insurers using the HurricanePools as a reinsurance vehicle. One purpose of financially penalizinglater investments is to obtain the greatest amount of money in theHurricane Pool as possible, by encouraging early investing anddiscouraging procrastination.

Financial investment unit prices are preferably higher when hurricanestrike probabilities are higher, and lower when hurricane strikeprobabilities are lower. Specific details of the pricing formula willpreferably be made available on the Hurricane Pools website, for thosewho may be interested. Factors influencing the pricing probabilitiesinclude the following:

1. The location of the county for which the investment is being made.For example, counties in south Florida are historically more likely tobe hit than are counties in Massachusetts, on average, and so financialinvestment unit prices for Florida counties will usually be higher.

2. The size of the county. Larger counties present bigger targets, andso financial investment units in larger counties will generally be morecostly.

3. Which of the Hurricane Pools an investment is made in. For example,financial investment units in Hurricane Pool #2 cost less than financialinvestment units in Hurricane Pool #1, other factors being equal,because it is more likely for one U.S hurricane to occur in a given yearthan for two such events to occur.

4. The location(s) and strength(s) of tropical cyclones in the AtlanticOcean, Caribbean Sea, and/or Gulf of Mexico, that potentially threatenthe United States. Such storms in some locations are more likely toaffect particular counties as hurricanes, based on a historicalclimatological analysis of more than a century of hurricane data, andfinancial investment unit prices for such counties will increaseaccordingly. Once a tropical depression is announced by the NationalHurricane Center, and continuing through the intensification of thestorm, financial investment unit prices continue to increase each time astorm is upgraded in strength, because threats to land are larger forstronger storms. This aspect of the financial investment unit pricing isintended to prevent persons who now have knowledge of a currentlyexisting storm from being unfairly rewarded by having this information,relative to early Hurricane Pool market participants.

C. Opening and Closing Hurricane Pools

The number of Hurricane Pools that may be opened to investment is at thediscretion of the Hurricane Pools management or provider. It isanticipated that two or three Hurricane Pools will be opened on January1st of each year. These Hurricane Pools pertain to possible U.S.hurricane landfalls during that calendar year, whether or not they occurduring the generally recognized “hurricane season” (June 1st throughNovember 30th). At the discretion of the Hurricane Pools Administrators,additional Hurricane Pools may be opened before the beginning of the“hurricane season,” for example if an unusually large number ofhurricanes may be forecast to occur in that year. Similarly, additionalHurricane Pools may be opened to investment during the hurricane season,particularly if previously open Hurricane Pools have all been closed byhurricane landfalls (preferably, measured by the eye of the hurricanehitting land), or by imminent possible hurricane landfalls.

Hurricane Pools will preferably be closed to further investment when thestorm to which they pertain is sufficiently close to landfall, accordingto the current NHC Advisories for that storm. Preferably, persons shouldleave home and not participate in the Hurricane Pools activity, whentold to evacuate. The exact trigger for Hurricane Pool closingspreferably strikes a balance between public safety (not discouragingprudent evacuation by remaining open too long) and broad participation(not cutting off investments before a given storm is an imminentthreat). A possible compromise could be to trigger a Hurricane Poolclosure when its tropical cyclone is both at hurricane strength and hasgenerated NHC hurricane warnings for one or more of the counties forwhich Hurricane Pool investments may be made. In addition, forfast-moving and/or rapidly developing hurricanes, Hurricane Pools wouldbe closed when the operational estimate of its track, as published inthe relevant NHC Advisory, has traversed at least one of the countiesfor which Hurricane Pool investments may be made.

Because Puerto Rico and the U.S. Virgin Islands are relatively far fromthe U.S. mainland, a Hurricane Pool may be closed for these twoterritories without it necessarily being closed for the rest of the U.S.In such cases, financial investment units for counties in theconterminous U.S. that are subsequently traversed by the same storm athurricane strength will also qualify to receive payouts from thatHurricane Pool. However, a Hurricane Pool that is closed because ofstorm proximity to or landfall on the U.S. mainland will preferably alsoclose for Puerto Rico and the U.S. Virgin Islands.

III. Hurricane Pool Payouts A. Disbursements to Qualifying FinancialInvestment Units

Preferably, all of the money invested in a given Hurricane Pool, lessfixed percentages for participating state governments (to help supportemergency management efforts) and for Hurricane Pool management, isdivided equally among Qualifying Financial investment units. AQualifying Financial investment unit is a financial investment unitpurchased for a county that is subsequently hit by the hurricane towhich that Hurricane Pool pertains. Therefore early market participants,whose Qualifying Financial investment units were purchased relativelycheaply, will realize larger returns on their investments than willlater market participants, for whom the financial investment unit priceswere higher.

To the extent possible, disbursements from Hurricane Pools to holders ofQualifying Financial investment units will preferably be made by postingthe amounts to the credit card account from which the investment wasoriginally made. This mechanism has the advantage that the disbursementswill be available very quickly, to people who may need these financialresources for rebuilding or other hurricane-related expenses. Forexample, individuals who may be displaced by extended evacuation fromtheir homes may have especially acute needs for these payouts. Theseproblems are magnified by loss of jobs. It may be necessary to withholdportions of large disbursements on behalf of the IRS.

B. Determination of Qualifying Financial Investment Units

For the purposes of determining Qualifying Financial investment units inHurricane Pools, counties are considered to have been “hit” in oneinstance if the track of the center of the hurricane as determined fromthe NHC Forecast, Public, or Special Advisories for that storm (or, e.g.within, +/−20 nautical miles) passes through some portion of thatcounty. The basic information in the NHC Advisories that is used todetermine Qualifying Financial investment units in this exemplaryinstance are the storm positions (latitude and longitude) and strengths(maximum sustained winds), that are reported to have occurred atparticular times. These location points will preferably be connected bystraight-line segments (or, optionally curves calculated from a formulain operational use at NHC or otherwise made public and preferablymentioned by reference on the Hurricane Pool website). Financialinvestment units in counties traversed by a track so calculated, betweentwo consecutive positions at which the storm was at hurricane strength(maximum sustained wind of 64 kt, or 74 mph), will, in this instance, beQualifying Financial investment units. For this purpose, thegeographical extent of counties will be defined for example by theCartographic Boundary Files of the U.S. Census Bureau, that arepublished at http://www.census.gov/geo/www/cob/co2000.html. Thesedefinitions could also be modified to allow financial investment unitsin counties affected by stronger hurricanes (Category 2+ hurricanes, asindicated by maximum sustained winds reported in the NHC Advisories) toreturn a larger financial investment unit of Hurricane Pool assets totheir market participants.

Preferably, it should be pointed out to Market participants in HurricanePools that these rules for determining Qualifying Financial investmentunits have been somewhat idealized, relative to real-world hurricanebehavior, in the interest of having a promptly available, clear,explicit and automatic way of disbursing Hurricane Pool assets toQualifying Financial investment units. In particular, a few pointsshould be noted. The first point is that: there will often be countiesexperiencing hurricane-force winds and/or other hurricane impacts thatnevertheless do not qualify as having been “hit” according to thedefinition used by the Hurricane Pools. This will be the case especiallyfor the larger and more powerful storms. Hurricane Pool marketparticipants whose intention is to, in effect, supplement theirinsurance coverage are therefore encouraged to invest in surroundingcounties also. To encourage market participants to protect themselves,the Hurricane Pools site will automatically flash or change color forseveral counties which border the county initially selected and urge ourmarket participants to spread their investment to include surrounding(collar) counties. In this manner, the market participant will, in thisinstance, have greater opportunity to collect from the Hurricane Poolsactively if damage occurs, but the eye of the hurricane does not entertheir county.

The second point is that, because qualifying counties are determined onthe basis of storm positions only at particular, and possibly irregulartimes, small discrepancies between the calculated track (used todetermine Qualifying Financial investment units) and the actual track(as determined some months later in the official NHC Tropical CycloneReport for that storm, or that might be evident at the time of the stormfrom a events of weather-radar images, for example) can and will occur.Again, it may be advisable for some individuals to invest in nearbycounties, in addition to the county(s) in which they have the mostinterest.

As a third point, the U.S. Census Bureau data files are onlyapproximations to the true geographical outlines of many counties. Theyconsist of a collection of line segments, and so will not accuratelyfollow curving county boundaries. In addition, portions of some counties(particularly relatively small islands) are not included in the CensusBureau's Cartographic Boundary Files. For example, the Dry Tortugas arenot included in the Cartographic Boundary File for Florida, so that ahurricane passing over this portion of Monroe County, Fla., would not byitself constitute a “hit” on Monroe County for the purpose ofdetermining Qualifying Financial investment units.

In cases where there may be multiple tropical cyclones in existence atthe same time, an explicit rule deciding which storm pertains to whichHurricane Pool is needed, if more than one of them eventually affectsthe U.S. as a hurricane. Priority can be determined according to thetime of landfall on at least one of the counties for which HurricanePools investments may be made. For example, if the hypotheticalhurricane “Bob” makes U.S. landfall ahead of hypothetical hurricane“Alice,” “Bob” would be assigned to Hurricane Pool #1, and “Alice” wouldbe assigned to Hurricane Pool # 2.

It is anticipated that payouts to Qualifying Financial investment unitswill be made within two weeks of the final NHC Advisory for the storm inquestion. In unusual cases, such as for storms that may have thepotential to reintensify and affect the U.S. again, Hurricane Poolpayouts may be delayed beyond two weeks at the sole discretion of theHurricane Pools Administrators. In all cases, Hurricane Poolsdisbursements will preferably be made on the basis of the best and mostrecent information available from the National Hurricane Center at thattime about the storm in question, and will not be subject to revision inthe event of subsequent updates to that information.

IV. The Hurricane Pools Website

With reference to FIGS. 13-18, the Hurricane Pool's activity, in oneinstance, will be administered through a website that calculatesfinancial investment unit prices (or prices of other financialinvestment units) automatically, according to information from NHCAdvisories that are updated at least 4 times daily when one or moreAtlantic tropical cyclones are present, and receives payments frommarket participants' credit card accounts, or other financialequivalent, or other alternatives to payment, such as transactions to anmarket participant's brokerage account. Preferably, first-time entrantswill need to register. Password protection will preferably be employedfor credit-card accounts associated with each registration, tofacilitate any eventual payouts that may need to be made to thataccount. Social Security information will preferably be required as partof the registration, in order for state and national government agenciesto track tax liability on any payouts. Other arrangements could be madefor those who access the website through their brokerage service orother third party service.

Current financial investment unit prices for all available counties canbe displayed both graphically and in tabular form. With reference to theschematic screen depictions of FIGS. 14 and 15, clickable maps (coastalarea and individual state) are made available, with financial investmentunit prices indicated approximately with a color code. Preferably,state-by-state pull down menus (not shown) are also provided.Participants are to be given the option of specifying their entrieseither in terms of financial investment units bought, or dollars to beentered, for each county selected. Choices made by a participant areshown in shaded form in FIGS. 14 and 15.

The sums entered to date in each Hurricane Pool (and available forsubsequent payout) will be posted on the Hurricane Pools website andcontinuously updated. For Hurricane Pools that are currently open forinvestment, it will be possible for site visitors to determine potentialpayouts for a financial investment unit in any county, under variousassumptions about the track of the hurricane to which that HurricanePool pertains. These “what if” calculations can be made available forany historical hurricanes that have crossed a county in question, or forany hypothetical hurricane track that a website visitor might beinterested in.

For Hurricane Pools that have been closed to further investment, theactual hurricane track and Hurricane Pool payouts per financialinvestment unit will preferably be listed, together with a variety ofofficial NHC information about that storm. Until a given tropicalcyclone has fully dissipated, and so has no chance of reintensifying andsubsequently affecting a portion of the U.S., these estimates will besubject to revision.

Because financial investment unit prices will be updated (preferably atleast four times daily according to the most current Advisoryinformation from NHC), it will be necessary for the site to beunavailable for accepting investments for short, pre-scheduled, periodsof time (e.g. every 6 hours). When an Atlantic tropical cyclone isrelatively close to the U.S., these blackout times will be morefrequent, in order to accommodate the additional NHC Advisories and toperform other necessary duties. In addition, some or all of the parts ofthe website may close from time to time on an unscheduled basis, inorder to incorporate new information that is occasionally provided byNHC at times other than the usual Advisory schedules. These additionalblackout periods will also allow time for the new information to bedisseminated to interested parties. In one instance, the lengths ofwebsite blackout times will depend on the speed with which the NHCadvisories can be obtained, and their information transformed to updatedhurricane probabilities for the Hurricane Pools. Even when there are noAtlantic tropical cyclones in existence, financial investment unitprices will preferably be updated during the regular (e.g. 6-hourly)blackout periods, with decreasing of the early-entry discount by a smallamount.

When choosing to purchase financial investment units for a particularcounty or neighboring counties, it is preferable to encourage marketparticipants to thoroughly familiarize themselves with as much data onhurricanes as is publicly available. To assist in this effort, helpfulweather-related links may be provided on the Hurricane Pools website, aswell as other educational information that might be helpful. Forexample, a graphical history of storms which have occurred during thelast 113 years and their associated tracks may be provided to marketparticipants and other participants.

With reference to FIGS. 24-40, further details concerning the websiteare considered. In FIGS. 4-40 further examples of systems and methodsaccording to principles of the present invention is shown employing oneor more graphical user interfaces. As will be appreciated by thoseskilled in the art, the graphical user interfaces may be constructedusing known computer programs and programming languages. In general, thegraphical user interfaces are employed to facilitate investment relatedactions by a user, such as investment research, trial calculations andother activities and implementing financial investment decisions. Thegraphical user interfaces include, in addition to descriptive andinformation data, active graphical items, such as “buttons” having aconventional shape (e.g. round, oval) as well as special shapes (e.g. acounty map or a storm track).

In the examples given, the financial activity relates to naturallyoccurring events of the types mentioned herein, such as tropical stormactivity. As will be seen, it is generally preferred that the financialactivity be related to defined geographical areas (herein referred to as“regions”), represented in map or table form. For example, the regionsdefined in various embodiments of the present invention may correspondto well-known geographic or political boundaries, such as county,township or parish borders. However, it is sometimes expedient to definea region as an arbitrary geographical area, unrelated, or only looselyrelated to established boundaries. As will be appreciated, althoughregions having the approximate size of counties or parishes arepreferred in the illustrated examples, regions can be of virtually anysize desired, smaller than a county or alternatively, larger, such asgroupings of several counties. Further, although the illustratedembodiments are concerned with coastal regions of the United States,virtually any land are could be used as well. Also, although theillustrated embodiments pertain to first land strike of hurricane stormson the continental U.S., other natural peril events, such as theearliest official designation of a designated area being flooded, arealso contemplated.

Turning now to FIG. 24, a system and method for financial activityemploying a graphical user interface is shown illustrating anintroductory page generally indicated at 610. Included are activegraphical selection item in the form of buttons 612 of various text andgraphic types. The buttons 612 provide links to a further detailed entrypage illustrated in FIG. 25. Also shown in FIG. 24 are descriptive datacomponents of the graphical user interface indicated at 614 and linkingcomponents indicated at 616 that invoke outside resources that areexternal to the embodiment of the invention described herein. Ifdesired, the linking components could be internalized to the inventionbeing described, if the system operator should choose to undertake thatadditional responsibility.

Referring now to FIG. 25, an entry page is shown. Included are activegraphical selection items or buttons 620, 622. Preferably button 620 isautomatically selected when the entry page is loaded, although button622 or neither button could be initially selected. In the preferredembodiment button 620 activates a data display showing probabilities forvarious land regions in real time. Included in the graphical userinterface, is a passive or static component in the form of a map 630 ofthe U.S., including eastern and southeastern coastal areas divided intoregions 632. These regions are overlaid by active graphical selectionitem or buttons 634 corresponding to the shape of the correspondingregion 632. Also included is a component of the graphical user interfacegenerally indicated at 638. This component is provided in the form of atable, with regions listed in one column, and their correspondingprobabilities listed in the adjacent column. The tabular component 638is preferably populated with active graphical selection item or buttonsin the form of text table entries, which serve as alternative activegraphical selection items to the graphical buttons 634.

Also included in the entry page of FIG. 25 are data components thatprovide information to the user. For example, data component 624provides a textual description of the real time map and relatedinformation displayed. Data component 626 provides textual descriptionof the current natural peril event status. At the time shown, a quietcondition is indicated with no ongoing storm having begun and no stormshaving occurred for the time period of the financial activity. Thepresent invention contemplates that the time period of the financialactivity may be defined in any manner desired. For example, the timeperiod could be the current calendar year, or the storm season for thecalendar year (e.g. June to November). Also contemplated are a number ofconsecutive time periods referred to herein as “events,” defined hereinas beginning at the year or season and ending, for example, with thefirst landfall of the year (defined according to preselected rules), andbeing immediately reset upon first landfall to start a second event forthe year, and so forth.

Referring now to FIG. 26, operation of button 634 is illustrated. Asmentioned, button 634 comprises one example of an active graphicalselection item. The button 634 may be activated as desired, by a keypress for example, or by merely moving the cursor over the button (anintuitive operation, owing to the graphical content of the button).Indicated in FIG. 26 is activation by moving the cursor over a button634 corresponding to a particular region defined by the financialactivity, corresponding to the geographical boundary of Charleston, S.C.The graphical user interface preferably responds in at least two ways.First, an information component in the form of a pop-up message 644appears next to the selected region.

The pop-up message 644 can contain virtually any desired messagecontent. Preferably, the message contains the probability of a firstland strike for the real time indicated in data component 624. Alsoincluded in pop-up message 644 is other data related to the financialactivity, such as the text name of the region selected and its inclusionin a regional grouping larger than county. As mentioned throughout thefigures and the examples of preferred embodiments, the probability offirst land strike is monitored by the facilitator of the financialactivity and is made available to the participants in a number ofdifferent ways. In place of the first land strike probability or inaddition thereto, the financial activity could monitor disasterestimates, in real time or on a historical basis, for example. Suchestimates could be calculated from meterological and other types ofdata, but could also be obtained from risk modeling companies and damageestimate services. For the selection illustrated in FIG. 26, the regionselected happens to correspond to a single county, and not part of alarger-sized geographical portion, and accordingly is designated as an“Individual County.” Also, characterization data related to theprobability is given in the pop-up message, indicating that the basisfor the probability as “historic,” although other bases could beemployed as well. The probability can be calculated in real time, inresponse to the user selection, or alternatively, can be extracted froma look-up table of previous calculations.

In the preferred embodiment, the graphical user interface responds tothe region selection by adjusting the tabular component 638 to displaythe text button corresponding to the chosen region in the middle of thetable, for ready contextual reference. In the embodiment illustrated,entries in the tabular component 638 are ranked according to decreasingprobability values, although virtually any ordering or arrangementdesired could be employed as well. Also, in the preferred embodiment,the same result could also be obtained by selecting the region's textualbutton 636, as opposed to the graphical button 634.

In the preferred embodiment, by selecting the desired region with amouse press, the graphical user interface responds by enlarging aportion of the display showing the selected region and its surroundingregions, in the manner shown in FIG. 27. In this figure, the selectedregion is Palm Beach, Fla., designated by the financial activity as an“Individual County,” indicating that the region corresponds to thegeographical and/or political boundary of that county of the State ofFlorida. The pop-up message 644 appears, as before, with information forthe region selected, and the textual button 636 is highlighted in thetabular component 638, and centered in that table area. If desired,additional buttons (not shown) can be provided to afford the user theopportunity to place an investment for the selected region, and/or toselect the neighboring regions, or to select additional individualregions.

Referring briefly to FIG. 25, button 622 is provided so that the usercan select financial activities related to storm tracks and individualstorms that have been recorded, with their related data analyzed to theextent necessary. As indicated herein, the U.S. government providesofficial determinations relating to storm events. For example, theNational Hurricane Center publishes ongoing reports of specific stormactivity, starting when a storm is a tropical depression at sea,continuing when a storm increases in intensity to become a tropicalstorm, and then when the storm further increases in intensity so as tobe designated a hurricane. Further, when a storm approaches land, e.g.is within 24 hours (estimated) of reaching landfall, official advisoriesare published at regular intervals, and at the appropriate time,official forecasts are also published. This data is, by its nature,historic, although data points along the course of a storm (the storm“track”) are given in the context of real time of near-real timeannouncements, advisories and predictions. Typically this data iscarefully analyzed by one or more responsible government agencies, andis recorded for future use. In one aspect of the present invention, thisdata is made available to the financial activity user in acomprehensible form that allows a user to digest and correlate largeamounts of data, quickly and easily, using graphical andgraphics-related tools.

Referring now to FIG. 28, the illustrated display is preferably invokedby selecting button 622 in FIG. 25. Included in FIG. 28 is the map 630of the U.S. Any storm tracks for the current year would be shown, alongwith their corresponding table entries (to be explained herein). At thecurrent time, there are no storms to report. Note that data component624 is now blank, indicating that a user selection must be made toproceed further. Also included is an active graphical selection item inthe form of a pull-down table 650 that is initially selected to thecurrent year.

If desired, any preceding year or other desired time (such as a seasonalperiod, a date range, a recurring date or month) provided by thefinancial activity) can be selected. For example, referring to FIG. 29,the year 2005 is selected. In addition to the map 630 of the U.S., thetabular component 638 is populated with a listing of names of stormsthat are reported for the selected year 2005. Each entry in tabularcomponent 638 is an active graphical selection item button used toinvoke the menu sub-selection illustrated in FIG. 30. FIG. 29 also showsa number of active graphical selection item buttons 666 in the graphicalform of storm tracks, i.e. paths of storms reported in the selected timeperiod (herein the year 2005). The same result is achieved by eitherselecting the storm track button 666 or the textual storm name buttonsin the tabular component 638 of FIG. 29.

Referring now to FIG. 30, in the preferred embodiment, for each storm anoption is provided to either “Load track and forecast advisories”according to text button 660, or “Explore probabilities for this storm”according to text button 662. Note that data component 624 now indicatesthe current selection of the storm “Katrina” in year 2005.

If text button 660 in FIG. 30 is selected, then the track and forecastadvisories are loaded for the selected storm in the selected timeperiod, and the display of FIG. 31 is presented to the user. In additionto showing the tabular component 638, with its indication of theselected storm, the storm tracks of FIG. 30 are replaced with a singlestorm track 670 for the selected storm, shown in an expanded (enlargedwidth) size, and with a plurality of data points 672, for the point intime indicated in pull-down table. The data points may include, forexample, official advisories, such as NHC advisories, other warning orinformation services provided by the NHC or other third partyinformation source. In the illustrated embodiment, NHC advisories arethe preferred data points.

If text button 660 in FIG. 30 is selected, then the track and forecastadvisories are loaded for the selected storm in the selected timeperiod, and the display of FIG. 31 is presented to the user. In additionto showing the tabular component 638, with its indication of theselected storm, the storm tracks of FIG. 30 are replaced with a singlestorm track 670 for the selected storm, shown in an expanded (enlargedwidth) size, and with a plurality of data points 672 for the point intime indicated in pull-down table. The data points may include a varietyof different data types, such as forecast advisories or other forecastproducts by the NHC or other responsible government agency. In thepreferred embodiment, the active graphical selection item table 676contains a list of storm advisories published by the NHC for theselected storm. Each storm advisory has a textual button 678, preferablycorresponding to available storm track data sets that have been reportedfor each advisory published. Initially, the first table item isselected, and the corresponding data points appear as active graphicalselection item buttons 672. When buttons 672 are selected, correspondingdata (not shown) is displayed, including, for example, current (i.e.current as of the time of the advisory) storm location, direction, pathvelocity, internal wind velocities and other storm relatedmeteorological and climatological data.

Any of the textual advisory name buttons 678 of FIG. 31 can be selected,as desired. Referring to FIG. 32, the sixteenth advisory for theselected storm has been selected, #016, occurring at Sat, August 27th 9AM. Preferably, the overall track outline has been retained, but thedata points along the track have been updated. For example, data point682 indicates the “present” location of the storm, now designated ashurricane Katrina. Data points 684 indicate past advisory data points,whereas data points 686 indicate forecast advisories. FIG. 33illustrates the user selection of data for the data point 682 for the(historically) current position of the storm. Selection of the activegraphical selection item button 682 causes data component 690 to bedisplayed. A similar operation is illustrated in FIG. 34 where forecastadvisory button 686 is selected, with the graphical user interfaceresponding by displaying information component 692. FIG. 35 shows the27th advisory data set that occurred approximately at the time oflandfall. Data point 694 shows the historically current location ofhurricane Katrina. Note that the 36 hour forecast advisory data point696 lies outside the storm track 670, indicating that the hurricanelevel was downgraded approximately 30 hours beyond the selected point intime (i.e. the time of advisory 27 of the 2005 storm Katrina).

FIG. 36 illustrates the path predicted for the storm at Sat, August 27th3 PM. Note the predicted track 670 stopping at the southern tip ofIllinois, slightly after the passage of 96 hours beyond the historicallycurrent time. This figure illustrates how forecast conditions, stormevent probabilities, vary during the course of a storm. In FIG. 36,strike probabilities are listed in tabular component 638 for thisselected point in time. If desired, any of the advisory time pointslisted in table 676 could be chosen, and in response, the graphical userinterface will prepare probability data. If desired, this data can beprepared for all regions available to a user, or the program canwait-until the user selects a particular region. Either the regionprobabilities can be calculated in real time, or previously calculatedvalues can be extracted from available databases or other recordsavailable.

FIG. 37 illustrates the probability of first landstrike for a selectedgeographical location or region, for a particular day and time inhistory, within the context of a given storm occurring in the chosenyear. An information component in the form of a pop-up message 710appears next to the selected region. Adjacent table 712 displays aranking of probabilities (and optionally, other data, not shown) forregions in play at the selected date and time in history. The table 712preferably displays a list of textual buttons representing the names ofthe regions whose data is accessible to the user.

FIG. 38 illustrates the probabilities of first landstrike for allregions in play, as of a chosen date and time when forecast dataavailable through the textual button 718, applies. As indicated, acomplete set of probability data is made available to a user who isstudying the investment conditions that existed for an actual storm,located at the position indicated at 720. Included in the data madeavailable to the user, is the National Hurricane Center 12 hour forecastadvisory, as indicated above, with reference to textual button 718.

As mentioned above with respect to FIG. 26, the graphical user interfaceoperating in real time, or near-real time, responds to the regionselection by adjusting the tabular component 638 to display the textbutton corresponding to the chosen region in the middle of the table,for ready contextual reference. In the embodiment illustrated in FIG.26, entries in the tabular component 638 are ranked according todecreasing probability values, although virtually any ordering orarrangement desired could be employed as well. As indicated in thesingle column listing of probabilities for corresponding regions, only asingle probability is associated with each region is contemplated forthe current storm season. Referring now to FIG. 39, multipleprobabilities (i.e. three) are displayed for each region.

The arrangement of FIG. 39 reflects a financial activity in whichseveral events are conducted for a given storm season. A number ofpossibilities exist. Preferably, at the beginning of the year, somesmall number (e.g. three) events are opened and operated concurrently.In the event of a first hurricane landfall, the first of these isclosed, and the remaining two continue—they are preferably not initiallyopened at that time, as set out in the following example where, as soonas the first landfall occurs in a given storm season, the first eventsis closed, and a second events is declared open. Under this latter modeof operation, the number of events offered by a financial activity for agiven storm season is determined by natural peril events, with thefinancial activity responding to each land strike in the mannerindicated. The table component 724 indicates that three events haveoccurred at the moment in time indicated. As mentioned, it is generallypreferred that this moment in time displayed is as close to real time aspossible. In FIG. 39, the probabilities for the first three events aretabulated in columns 730, 732 and 734. Other financial datacorresponding to each region listed in the table is also displayed. Forexample, a theoretical return on investment (assuming an immediate firststrike in the region of interest) is given in column 738, a currenttotal investment is given in column 740 and a per-financial investmentunit purchase cost is indicated in column 742. Additional data items canbe included, either in the spreadsheet style illustrated in FIG. 39, orin a pop-up or pull-down style, for example, as may be desired.

Turning now to FIG. 40, activities pertaining to a purchase of afinancial investment are illustrated. An information component in theform of a pop-up message 748 appears next to the selected region.Message 748 may include probability data, as indicated and/or additionalinvestment data, such as meteorological data. Table component 752supplies additional data as may be necessary. For example, in additionto providing a textual confirmation of the region selected, the currenttime, hypothetical rate of return (assuming an immediate strike in theregion selected) and financial investment unit cost are displayed to theuser. If the user should decide to proceed, the number of financialinvestment units to be purchased are entered, and the total cost for thetransaction is displayed. Alternatively, the user may enter a financialamount, and the programs returns the number of financial investmentunits that can be purchased for the designated amount. As a final step,the user activates button 756 to finalize the offer to purchase. If theuser wishes to explore operation of the financial activity, but alsowishes to make certain that an offer to purchase is not tendered, theuser can activate button 762, requiring the user to clear the “trialrun” status previously chosen, before proceeding with an actualtransaction. This causes a display component 763 to appear with avariety of information, relevant to the user's current proposedposition.

FIG. 41 shows display component 763 in greater detail. Preferably,display component 763 is provided in the form of a table displaying avariety of data relevant to the user's proposed position, should thedesignated number of financial investment units be purchased. Includedis a Landfall Instantaneous Return Calculation, assuming that the stormimmediately makes landfall. Following, is a calculation of a LandfallConditional Floor, setting out the amount the user can expect to receiveif the storm should eventually hit the designated geographical area. Avariety of secondary market information is also reported to the user,including the current value of the proposed investment in the secondarymarket, based on market trading. The bid price, asking price and numberof available financial investment units are also given.

The present invention also contemplates that the display component 763is made available to users when a user logons onto the system at a laterdate. The display component is updated, either automatically, or inresponse to a key press to keep the user informed of his position in themarket. FIG. 42 shows a summary display of the user's market status,assuming the user has invested in a number of different positions,schematically indicated by display components 763 in FIG. 42. A totaldisplay component 770 resembles the individual display components 763,except for showing a total of their data components.

V. Disposition of Hurricane Pool Assets when No U.S. LandfallingHurricane Occurs

It is generally preferred that a “null” event be created as analternative to a selected geographical region. When employed, the nullevent is an investment option provided as an alternative to allgeographical areas, and indicates the participant's prediction that nohurricane landfall (or occurrence of another natural peril event) willoccur for a given financial activity time period.

As mentioned herein, it is possible that an entire year or other periodof financial activity can pass without a landfall occurrence. Whilevarious arrangements can be provided under exchange rules, it isgenerally preferred to account for this possibility as an option choice.It is preferred that the option choice be presented for trade as if itwere an eligible county or other geographical region. Financial activityrules are preferred that provide for payouts to holders of the nullcounty only at the conclusion of a financial activity period, such as ameteorological hurricane season,” generally considered to be December 1of the current year. If no hurricane makes landfall in the U.S., duringthe hurricane season, for example, the null county holders for allevents or other activities of the season will preferably receive a payout from a portion of the monies collected.

It can happen that a Hurricane Pool will be closed by the imminentapproach of a hurricane which subsequently fails to pass over any U.S.land area, according to the definition of a “hit” used by the HurricanePools (e.g. Hurricane Ophelia (2005) would have been one such case). TheHurricane Pools need to have a clear and automatic rule for thedisposition of the assets of such Hurricane Pools. Some possibilitiesare:

1. Preferably, a fund closed by an imminent approach of a storm thatdoes not make landfall is, to reopen that events when it is clear fromNHC or other official reports that the storm in question poses nofurther threat.

2. Transfer all assets and financial investment unit ownerships to thenext Hurricane Pool. For example, if Hurricane Ophelia had closedHurricane Pool #3 in 2005, all investments made in Hurricane Pool #3would be transferred to Hurricane Pool #4. Financial investment units inHurricane Pool #4 would then include those reflecting previousinvestments in Hurricane Pool #4, in addition to those purchased byinvestments in (the now closed) Hurricane Pool #3. Assets of thecombined Hurricane Pool #4 would then have been paid to financialinvestment units for counties qualifying according to the path ofHurricane Rita, regardless of whether they represented investments inHurricane Pool #3 or Hurricane Pool #4.

3. Transfer the assets, but not the financial investment unit ownership,to the next Hurricane Pool. Here, the money invested in Hurricane Pool#3 for the hurricane that eventually turned out to be Ophelia would havebeen transferred to Hurricane Pool #4 and paid according to the track ofhurricane Rita, but financial investment units purchased in the originalHurricane Pool #3 in this example, would not qualify for anydisbursements.

4. Another rule will be needed to govern assets of Hurricane Poolsremaining open at the end of the year. If desired, one of the aboveoptions, (although not necessarily the same as that governing mid-seasonHurricane Pool closures) or perhaps, some other option could be chosenfor pool disposition.

5. The pools can be returned to participants, less management costs, ifdesired.

6. Preferably, however, an additional outcome, called “null” event isdefined. For the Kth events, this corresponds, to the event whereinthere is no Kth U.S. hurricane landfall in the current year.Participants purchasing financial investment units in the null outcomesplit the pool of money at the end of hurricane season, if that eventsis still open as a consequence of a fund remaining open until that time.

VI. Detailed Consideration of the “Hurricane Pools” Example

I. Introduction

The following is a detailed consideration of the Hurricane Pools examplegiven above. In one example, the number of Hurricane Pools in whichplayers may participate varies from year to year. Initially, K HurricanePools are opened, beginning on 1 January of the year before thehurricane season in question. Each of these relate to one of the first Ktropical cyclones passing over a portion of the U.S. with at leasthurricane-force winds, as determined by the National Hurricane Center orits successors, during the hurricane season (1 June through 30November). In relatively active years, additional Hurricane Pools may beopened as the hurricane season progresses. The Hurricane Pools enteredin a given natural peril event, less portions for state participationand Hurricane Pool management, are paid to entrants according to aformula that accounts for the chances of each hurricane striking thequalifying county(s), as assessed at the time a participant entry ismade.

VII. Structure of the Hurricane Pools

A. One Example of Hurricane Pool Financial Investment Units

Entries (investments) in the Hurricane Pools may be made for individualcounties (including the null event, when present in the financialactivity), in the form of “financial investment units.” The price of afinancial investment unit varies in one instance, according to theprobability of a hurricane strike on the county for which the entry ismade, using information available at the time the entry is made, andmodified by a discount factor that encourages early entries andpenalizes later entries. Financial investment units are priced relativeto a benchmark, or “par” value, defined by an entry for the mostvulnerable county historically, (Palm Beach, Fla.) made at the beginningof the hurricane season (1 June). Choice of Palm Beach County as the parlevel is arbitrary because all of the financial investment unit valuesare relative; but this choice may have market participant appeal, inthat the prices of entries for all other counties will then reflect anapparent discount.

The reference probability for a hurricane strike on Palm Beach county,as well as reference probabilities for the other n counties for whichentries are accepted, has been derived from a climatological analysis ofU.S. landfalling hurricanes that occurred from the late 19^(th) centurythrough the present. This type of analysis can specify the probabilitythat the center of a hurricane-force tropical cyclone will pass within75 nautical miles (86.25 statute miles) of the county center in a givenyear. These values can be adjusted for the size of a county byestimating the probability that a hurricane will track through thecounty in a given year, assuming that the county has a circular shape.Defining the probability of passage within 75 n. mi. of county i asQ_(i), the size-adjusted annual climatological hurricane strikeprobability is, according to the following Equation (1):

$\begin{matrix}{{Q_{i}^{*} = {{Q_{i}\frac{2\left( {A_{i}/\pi} \right)^{1/2}}{2 \cdot 87.25}} = {0.006541\mspace{14mu} A_{i}^{1/2}Q_{i}}}},} & (1)\end{matrix}$

where A_(i) is the area of the county, in square statute miles. The87.25 mile counting radius is used to smooth the somewhat erratichistorical record of hurricane tracks.

Referring now to FIG. 19 a schematic diagram indicates a preferredtreatment of a geographical unit, herein, Palm Beach county, FL, with anarea of approximately A=2230 sq. mi., represented by a circle of thesame area (dashed). Hurricane centers passing within 86.25 miles of thecounty center (long arrows) have a probability of about 0.31 (ratio ofthe dashed circle diameter to 172.5 ml) of passing through the countyitself.

FIG. 19 illustrates the geometry behind Equation (1), for the case ofPalm Beach County. The area of this county is approximately A=2230 sq.mi., and the annual probability of a hurricane track within 86.25 mi. ofthe county center is Q=28.74%. Many storms tracking within this distanceof the county center will fail to pass through the county, but theproportion that will do so is given approximately by the ratio of thediameter of the circle approximating the county (=2[A/□]^(1/2)=53.3 mi.)to twice the search radius defining Q, or 172.5 ml. Therefore, for thiscounty, Q*=28.75% (53.3/172.5)=8.88%. The counties included in theHurricane Lottery, their approximate areas, and their Q and Q*climatological values are calculated and made available for futurereference.

The reference probability for a hurricane strike on Palm Beach county inany single Hurricane Pool is smaller than Q*/100=0.0888, because thereare more than one U.S. hurricane landfalls in an average year. Thisaverage number of U.S. hurricane landfalls is □=1.7 hurricanes/year, sothe Palm Beach County reference probability is, according to thefollowing Equation (2):

$\begin{matrix}{p_{ref} = {\frac{Q^{*}}{100\; \mu} = {\frac{8.88\%}{(100)(1.7)} = {0.0522.}}}} & (2)\end{matrix}$

In addition to depending on hurricane likelihoods for a county ofinterest in relation to the reference probability for Palm Beach countyin Equation (2), financial investment unit prices also increasegradually through the time period that entries are accepted, accordingto daily compounding of an annualized discount rate D that is multipliedin the financial investment unit pricing formula, according to thefollowing Equation (3):

$\begin{matrix}{{{Time}\text{-}{of}\text{-}{entry}\mspace{14mu} {adjustment}} = {\left( {1 + D} \right)^{\frac{{j\; {date}} - 152}{365}}.}} & (3)\end{matrix}$

Here jdate is the Julian date (consecutive numbering of the days of theyear), so that the exponent in Equation (3) is zero, and Equation (3)produces no change in the financial investment unit price, for 1 June(jdate=152). Julian days in the year prior to the hurricane season inquestion are negative. If the annual discount rate is 5%, then D=0.05.

Adjusting financial investment unit prices by multiplying by Equation(3) rewards early entries and penalizes late entries, in part as acompensation for opportunity costs. An appropriate value for thediscount rate D needs to be determined, and might be varied from year toyear to reflect values in then current financial markets. However, Dshould also include a very substantial premium over short or medium-terminterest rates in order for this factor to have a significant effect onfinancial investment unit prices, and so to encourage contributions tothe Hurricane Pools well in advance of the beginning of hurricaneseason. Referring now to FIG. 20, a graphical plot shows financialinvestment unit price, relative to par on 1 June, for five values of theannual discount rate, D. FIG. 20 indicates values of Equation (3) as afunction of date of entry into the Hurricane Pool, for a range of valuesof D. The relative financial investment unit price is 1.0 for alldiscount rates at the par date of 1 June. For current market rates onshort-term money (D 0.04, or 4%) the effect on financial investment unitprice, shown by the dashed line, is negligible. An annual discount rateof D=4.0 (i.e., 400%) is necessary to produce (for example) a pricedifferential of approximately 15% between 1 May and 1 June.

The price per financial investment unit for a particular county, i, isdetermined by the probability of a hurricane strike on that county,p_(i), at the time the entry is made; and in relation to the par valuefor an entry on Palm Beach county (Equation 2) as of 1 June (Equation3). These factors are combined to determine the financial investmentunit price using the following Equation (4):

$\begin{matrix}{{{Price}\mspace{14mu} {per}\mspace{14mu} {share}} = {{F\left( {1 + D} \right)}^{\frac{{j\mspace{14mu} {date}} - 152}{365}}{\frac{\ln \left( {1 - p_{i}} \right)}{\ln \left( {1 - p_{ref}} \right)}.}}} & (4)\end{matrix}$

This equation is the basic pricing tool for the Hurricane Pools. Here Fis an arbitrary pricing factor, that could be chosen according tomarketing considerations. It is the par price for one financialinvestment unit, for Palm Beach County on 1 June. For example, F=1corresponds to $1/financial investment unit. A higher pricing factor,such as F=100 ($100/financial investment unit) might have the effect ofsubtly encouraging some participants to enter more money in theHurricane Pool. The second factor in Equation (4) specifies that entriesmade before 1 June will be cheaper, and entries made after 1 June willbe more expensive, as indicated in Equation (3) and in FIG. 20. FIG. 21,table 1, shows an example of illustrative financial investment unitprices, in round numbers, for a range of strike probabilities p_(i),assuming purchase on 1 June, with F=$100/financial investment unit.

Finally, Equation (4) indicates that the financial investment unit pricefor county i depends on the probability p_(i) relative to the referenceclimatological probability p_(ref) for Palm Beach county, through thefunction −ln (1−p). This functional form has been chosen in order toobtain financial investment unit prices that are economically logical,particularly toward the extremes of the probability range. For p_(i)=0,Equation (4) produces a zero financial investment unit price: financialinvestment units in a county are free if there is absolutely no chancefor the Hurricane Pool to pay off for that county, and financialinvestment units are extremely cheap for counties where theprobabilities of being affected by hurricanes (e.g., in west Texas) arevanishingly small. At the other extreme, the financial investment unitprice approaches infinity as the probability that a hurricane willaffect the county approaches 1, so that the Hurricane Pools offer noreward for betting on a sure thing. FIG. 21, table 1 shows thedependence of financial investment unit prices (purchased on 1 June,with F=$100/financial investment unit) on the strike probability p_(i),for a few illustrative cases. According to equation (4), unless thereare Atlantic tropical cyclones currently in existence, counties forwhich the climatological probability Q_(i)*/(100μ)=p_(i)<p_(ref) (i.e.,all counties except Palm Beach), the price per financial investment unitwill be less than F, and accordingly most participants will receive adiscount in the purchase price.

VIII. Determination of Strike Probabilities for Equation (4)

The hurricane strike probabilities p_(i) in Equation (4) are based onthe best information available at any given time, that can reasonably beobtained in an automated way by the Hurricane Pool's website software.If no Atlantic tropical cyclones are in existence at the time of aHurricane Pool entry, that best information will be the unconditionalclimatological probability of a hurricane strike on the county inquestion for the k^(th) Hurricane Pool. These will be referred to in thefollowing as “Stage I” probabilities.

Sharper, that is, more detailed, or more accurate or better informedprobability information about hurricane strikes can be obtained when oneor more Atlantic tropical cyclones are in existence, but are too farfrom the U.S. for probability forecasts of hurricane-force winds forcounties of interest to be issued by the TPC. In such cases, theprobabilities p_(i) in Equation (4) are obtained from climatologicalvalues for each county, conditional on the existence of a tropicaldepression, or tropical cyclone such as a hurricane, in a given sectorof ocean. These conditional climatological probabilities will bereferred to as “Stage II” probabilities. In another example, pricing maybe determined solely, or partially by market activity, in combinationwith other factors described herein.

Finally, the TPC issues probability forecasts for hurricane-force windsduring the upcoming 5 days. These forecasts provide the “Stage III”probabilities, when they extend over land areas of interest, especially,when they predict landfall within the next 24 hours. To the extent thatthere may be more than one Atlantic tropical cyclone in existence at agiven time, Stage II and/or Stage III probabilities for each need to becombined in order to evaluate p_(i) in Equation (4). In one example,Stage I pricing is determined according to the probabilities and otherconsiderations provided herein, whereas Stage II and Stage III pricingis determined solely by market activity.

A. Stage I Probabilities

The Stage I probabilities are obtained from climatological values, in away that follows Equation (2) for the reference strike probability forPalm Beach county. In Equation (2), the size-corrected annual strikeprobability Q* is divided by the average number of strikes per year, μ,to reflect the fact that more than one hurricane affects the U.S. peryear, on average, and is converted from percentage to fractionalprobability. The Stage I probabilities are further corrected to reflectthe fact that, for the second and subsequent Hurricane Pools, it is lesslikely for there to be a corresponding U.S. hurricane landfall. That is,entering the first Hurricane Pool is less uncertain than is entering thesecond Hurricane Pool with respect to the Stage I probabilities, and sothe financial investment unit prices for the first Hurricane Poolsshould be higher. Similarly, the financial investment unit prices shouldbe higher for the second Hurricane Pool than for the third and anysubsequent Hurricane Pools. These adjustments are included in thecalculation of the Stage I probabilities using probabilities fordifferent numbers of landfalling hurricanes, as calculated using thePoisson distribution. This distribution is a conventional andwell-accepted probability model for allocating probability among thepossible numbers of hurricanes in a given year when the average numberper year is μ. Specifically, the Poisson probabilities for each possiblenumber, X, of U.S. landfalling hurricanes are, according to Equation(5):

$\begin{matrix}{{{\Pr \left\{ {X = x} \right\}} = \frac{\mu^{x}e^{- \mu}}{x!}},{x = 0},1,2,\ldots} & (5)\end{matrix}$

Using these Poisson probabilities with μ=1.7 U.S. landfalling hurricanesper year, on average, the Stage I probabilities for the i^(th) county ink^(th) Hurricane Pool are, according to the following Equation (6):

$\begin{matrix}{{p_{i}^{(1)} = {\frac{Q_{i}}{100\mspace{14mu} \mu}\frac{\Pr \left\{ {X \leq k} \right\}}{1 - {\Pr \left\{ {X = 0} \right\}}}}},{i = 1},\ldots \mspace{11mu},{n.}} & (6)\end{matrix}$

When a Stage I probability is the appropriate risk estimate for countyi, p_(i) ^((I)) is substituted for p_(i) in Equation (4) to determinethe financial investment unit price. For the k=1^(st) Hurricane Pool,the ratio of Poisson probabilities in Equation (6) is 1, so thatEquation (6) for County i is exactly analogous to Equation (2) for thereference county, Palm Beach. That is, p_(ref) in Equation (2) isnothing more than the Stage I probability for Palm Beach county in thefirst Hurricane Pool. For the second and subsequent Hurricane Pools,these Stage I probabilities are reduced to reflect the fact that thecorresponding hurricanes are less likely to occur. The purpose of thissecond factor in Equation (6) is to provide a further price advantage toearly entrants in the second and subsequent Hurricane Pools, which maynot pay off at all, relative to entrants who wait until after theformation of what may become the k^(th) landfalling hurricane beforeentering. FIG. 22, table 2 shows Poisson probabilities from Equation(5), calculated with μ=1.7 landfalls/year, the corresponding cumulativeprobabilities Pr{X≦x}, and the ratio of probabilities on the right-handside of Equation (6). FIG. 22, table 2 shows Poisson probabilities forμ=1.7 hurricane landfalls per year, with corresponding cumulativeprobabilities and ratios of probabilities used in Equation (6).

B. Stage II Probabilities

When an Atlantic tropical cyclone is in existence, the Stage IIprobabilities p_(i) ^((II)) associated with county i being affected by ahurricane may increase from the respective Stage I value, depending onthe location and intensity of the storm. These Stage II probabilitiesare obtained by combining the Stage I probabilities, with conditionalclimatological relative frequencies of hurricane-force winds occurringwithin 120 n.mi. (138 statute miles) of each county center, given that atropical cyclone that is or will eventually become a named storm (i.e.,at least tropical storm strength) exists in one of 406 2.5 by 2.5 degreeregions of the Atlantic ocean, Caribbean Sea, or Gulf of Mexico. Theseconditional relative frequencies denote one of these ocean regions inwhich there is a tropical cyclone as j, and the conditional probabilitythat hurricane force winds due to this storm will eventually occurwithin 120 n. mi. of the center of county i as Q_(i,j). That is, foreach ocean region j, there is a data table similar to that for theunconditional climatological values Q_(i), although the conditionalQ_(i,j) climatological values are calculated with a larger smoothingradius (120 vs. 75 n. mi.) because there are fewer storms from which tocalculate the conditional relative frequencies. Accounting for thislarger smoothing radius, the size-adjusted conditional relativefrequencies Q*_(i,j) are calculated, analogously to Equation (1), usingthe following Equation (7):

$\begin{matrix}{{{Q_{i,j}^{*} = {{Q_{i,j}\frac{2\left( {A_{i}/\pi_{i}} \right)^{1/2}}{2 \cdot 138}} = {0.004088\mspace{14mu} A_{i}^{1/2}\mspace{14mu} Q_{i,j}}}};{i = 1}},\ldots \mspace{11mu},{n;{j = 1}},\ldots \mspace{11mu},406.} & (7)\end{matrix}$

Stage II probabilities are computed by combining these area-adjustedconditional relative frequencies with the corresponding Stage Iprobabilities, according to the following Equation (8):

$\begin{matrix}{{p_{i}^{({II})} = {p_{i}^{(I)} + q_{i,j} - {p_{i}^{(I)}q_{i,j}}}},{i = 1},\ldots \mspace{11mu},{n;{j = 1}},\ldots \mspace{11mu},{406;}} & (8)\end{matrix}$

where, according to the following Equation (9):

$\begin{matrix}{q_{i,j} = \left\{ \begin{matrix}{\frac{{.837}\mspace{14mu} Q_{i,j}^{*}}{100},} & {{if}\mspace{14mu} {the}\mspace{14mu} {storm}\mspace{14mu} {in}\mspace{14mu} {ocean}\mspace{14mu} {sector}\mspace{14mu} j\mspace{14mu} {is}\mspace{14mu} a\mspace{14mu} {unnamed}\mspace{14mu} {depression}} \\{\frac{Q_{i,j}^{*}}{100},} & {{if}\mspace{14mu} {the}\mspace{14mu} {storm}\mspace{14mu} {in}\mspace{14mu} {ocean}\mspace{14mu} {sector}\mspace{14mu} j\mspace{14mu} {is}\mspace{14mu} a\mspace{14mu} {tropical}\mspace{14mu} {storm}} \\{\frac{1.72\mspace{14mu} Q_{i,j}^{*}}{100},} & {{if}\mspace{14mu} {the}\mspace{14mu} {storm}\mspace{14mu} {in}\mspace{14mu} {ocean}\mspace{14mu} {sector}\mspace{14mu} j\mspace{14mu} {is}\mspace{14mu} a\mspace{14mu} {{hurricane}.}}\end{matrix} \right.} & \begin{matrix}\begin{matrix}\left( {9a} \right) \\\begin{matrix}\begin{matrix}\; \\\left( {9b} \right)\end{matrix} \\\;\end{matrix}\end{matrix} \\\left( {9c} \right)\end{matrix}\end{matrix}$

Here, 0.837 is the proportion of tropical depressions that have gone onto at least tropical weather strength (1991-2004, reflecting currentoperational practice at NHC), and 1.72 is the ratio (1886-1998) of thenumbers of tropical storms to hurricanes in the Atlantic basin. Thepurpose of Equation (9) is to reflect the fact that the existence of ahurricane is more threatening, on average, than the presence of atropical storm, which is in turn more threatening than the presence of atropical depression. The probability from Equation (8) is substitutedfor p_(i) in Equation (4) when the Stage II risk assessment isappropriate for county i.

Equation (8) reflects the increase in risk, over and above the baselinerisk to county expressed by p_(i) ^((I)), attributable to the presenceof a tropical cyclone in ocean sector j. The conditional probabilitiesq_(i,j) are combined with (rather than replace) the Stage Iprobabilities in Equation (8), because county i continues to be at(climatological) risk for being struck by a hurricane, even if the stormin ocean sector j fails to make landfall as a hurricane. If theconditional probability q_(i,j) is substantial, p_(i) ^((II)) will beappreciably larger than p_(i) ^((I)). If the tropical cyclone in oceansector j has negligible probability of affecting county i as ahurricane, Equation (8) implies p_(i) ^((II))≈p_(i) ^((I)).

C. Stage III Probabilities

Stage III probabilities will be based on the NHC hurricane windforecasts provided as part of the official advisory for each tropicalcyclone. The system that is expected to be in place for these forecastsfor the 2006, 2007, and later hurricane seasons (currently described byTPC as “experimental”) will produce probability forecasts for windspeeds of at least hurricane force within the upcoming 120 hours (aftereach advisory), when these probabilities are at least 2.5%. Examples areshown at www.nhc.noaa.gov/feedback-pws-graphics2.shtml?.

In the current TPC forecast, hurricane-force winds in county i aredenoted as f_(i). Analogously to Equation (8), the Stage IIIprobabilities are computed by combining these forecasts with the Stage Iprobabilities from Equation (6), again because failure of the currenttropical cyclone to affect the U.S. as a hurricane does not preclude thek^(th) Hurricane Pool from paying out for some subsequent storm.Specifically, the Stage III probabilities are computed using thefollowing Equation (10):

$\begin{matrix}{{p_{i}^{({III})} = {p_{i}^{(I)} + f_{i} - {p_{i}^{(I)}f_{i}}}},{f_{i} > q_{i,j}},{or}} & \left( {10a} \right) \\{{p_{i}^{({III})} = p_{i}^{({II})}},{f_{i} < q_{i,j}},} & \left( {10b} \right)\end{matrix}$

Equation (10b) includes the possibility that the storm in question mayaffect a county for which f_(i)=0, because these TPC forecasts are setto zero if the probability is smaller than 2.5%. Again the Stage IIIprobabilities from Equation (10) are substituted for p_(i) in Equation(4) when explicit TPC forecasts for hurricane-force winds are currentfor some portion of the U.S.D. Combining Stage II and Stage III probabilities

It can happen that two or more Atlantic tropical cyclones are inexistence at the same time. In such cases, their strike probabilitiesfor each county i need to be combined in some way, to yield the largerprobability that either one or the other might affect the county inquestion. Let p_(i)(1) be the probability of the first of these stormsfor county i, calculated using either Equation (8) or Equation (10), asappropriate. Similarly, let p_(i)(2) be the corresponding value for thesecond of these storms. If there are only two such cyclones present, thecombined probability p_(i) to be used in the pricing Equation (4) isobtained using the following Equation (11)

p _(i) =p _(i)(1)+p _(i)(2)−p _(i)(1)p _(i)(2).  (11)

This probability would be applied equally to the next two HurricanePools (assuming that there are two or more) that are still active andaccepting entries.If there is a third such tropical cyclone, denote its probability forcounty i, calculated from the Equation appropriate to its Stage, asp_(i)(3). The combined probability for county i in Equation (4) wouldthen be, according to Equation (12)

$\begin{matrix}\begin{matrix}{p_{i} = {{p_{i}(1)} + {p_{i}(2)} + {p_{i}(3)} - {{p_{i}(1)}{p_{i}(2)}} - {{p_{i}(1)}{p_{i}(3)}} -}} \\{{{{p_{i}(2)}{p_{i}(3)}} + {{p_{i}(1)}{p_{i}(2)}{{p_{i}(3)}.}}}}\end{matrix} & (12)\end{matrix}$

This probability would be applied to the next (up to) three HurricanePools still accepting entries.

IX. Closing Hurricane Pools

Hurricane Pools cease to be available for further entries when thecorresponding hurricane is sufficiently close to a U.S. land area.“Sufficiently close” could mean that either a hurricane watch orhurricane warning has been issued for a U.S. coastal county. BecausePuerto Rico and the U.S. Virgin Islands are relatively far from the U.S.mainland, a Hurricane Pool can be closed for these two territorieswithout it necessarily being closed for the rest of the U.S. Because ofthe prevailing westward tracks of tropical cyclones at low latitudes, aHurricane Pool that is closed because of storm proximity to the U.S.mainland is also closed for Puerto Rico and the U.S. Virgin Islands.

X. Payout Algorithm

Financial investment units purchased in the k^(th) Hurricane Pool forcounties traversed by the k^(th) U.S. landfalling hurricane are“qualifying financial investment units.” In one instance, thesecountries are defined by the NHC operational adversaries. In anotherinstance, these counties are defined as those containing a “best track”hurricane position, or a portion of a line connecting two “best track”hurricane positions, as portrayed in the “best track” Table of theofficial TPC Tropical Cyclone Report for that storm. Payouts arepreferably determined by dividing the available Hurricane Pools (e.g.participant entries less state and management percentages) by the numberof qualifying financial investment units, and paying that amount foreach qualifying financial investment unit.

In cases where there may be multiple tropical cyclones in existence atthe same time, priority is determined according to time of first U.S.landfall. For example, if the hypothetical hurricane “Alice” makeslandfall after hurricane “Bob,” “Bob” would be assigned to Pool 1 and“Alice” would be assigned to Pool 2.

It is anticipated that payouts to Qualifying Financial investment unitswill be made within two weeks of the final NHC Advisory for the storm inquestion. In unusual cases, such as for storms that may have thepotential to reintensify and affect the U.S. again, Pool payouts may bedelayed beyond two weeks at the sole discretion of the PoolsAdministrators. In all cases, Pools disbursements will be made on thebasis of the best and most recent information available from theNational Hurricane Center at that time about the storm in question, andwill not be subject to revision in the event of subsequent updates tothat information. In the event, however, that there is no landfallofficially reported for the season or other time period, a “null” eventcan be provided as an investment option, as described herein.

XI. Caveats Regarding Pool Payouts

The above rules for determining Qualifying Financial investment unitshave been somewhat idealized, relative to real-world hurricane behavior,in the interest of having a promptly available, clear, explicit andautomatic way of disbursing Pool assets to Qualifying Financialinvestment units. In particular:

-   -   There will often be counties experiencing hurricane-force winds        and/or other hurricane impacts that nevertheless do not qualify        as having been “hit” according to the definition used by the        Hurricane Pools. This will be the case especially for the larger        and more powerful storms. Pool market participants whose        intention is to, in effect, supplement their insurance coverage        will therefore be encouraged to invest in surrounding counties        also. To encourage market participants to protect themselves,        the Pools site will automatically flash several counties which        border the county initially selected and urge market        participants to spread their investment to include surrounding        counties. In this manner, which we call a “collar” the market        participant will have greater opportunity to collect pools if        damage occurs but the eye of the hurricane does not enter their        county.    -   Because qualifying counties are determined on the basis of storm        positions only at particular, and possibly irregular times,        small discrepancies between the calculated track (used to        determine Qualifying Financial investment units) and the actual        track (as determined some months later in the official NHC        Tropical Cyclone Report for that storm, or that might be evident        at the time of the storm from a events of weather-radar images,        for example) can and will occur. Again, it may be advisable for        some individuals to invest in nearby counties, in addition to        the county(s) in which they have the most interest.    -   The U.S. Census Bureau data files are only approximations to the        true geographical outlines of many counties. They consist of a        collection of line segments, and so will not accurately follow        curving county boundaries. In addition, portions of some        counties (particularly relatively small islands) are not        included in the Census Bureau's Cartographic Boundary Files. For        example, the Dry Tortugas are not included in the Cartographic        Boundary File for Florida, so that a hurricane passing over this        portion of Monroe County, Fla., would not by itself constitute a        “hit” on Monroe county for the purpose of determining Qualifying        Financial investment units.

XII. Website Features

The Hurricane Pool will preferably be run through a website thatcalculates financial investment unit prices automatically, according toinformation from TPC advisories that are updated four times daily.Accordingly, it may be necessary for the site to be unavailable foraccepting entries for short, pre-scheduled, periods of time every 6hours for example. In addition, the website may need to be able to closefrom time to time on an unscheduled basis, in order to incorporate newinformation that is occasionally provided by the TPC at other than thescheduled 6-hourly update times. The lengths of these website blackouttimes, if any, will depend on the speed with which the NHC advisoriescan be obtained, and their information transformed to updated hurricaneprobabilities for the Hurricane Pool. Even when there are no Atlantictropical cyclones in existence, financial investment unit prices will beupdated during the regular blackout periods, by incrementing the date,jdate in Equation (4), by 0.25, four times daily.

Preferably, first-time entrants will need to register. Passwordprotection may be preferred if a single credit-card account is to beassociated with each registration, in order for any eventual payouts tobe made to that account. SSN information is preferably made part of theregistration in order for the IRS (and possibly also some states) totrack tax liability on any payout. As an alternative, an outside servicecan provide credit or other financial services.

Current financial investment unit prices (or other financial investmentunit) for all available counties are preferably displayed bothgraphically and in tabular form. Clickable maps (whole-coast, andindividual state) are also preferably made available, with financialinvestment unit prices indicated approximately with a color code.State-by-state pull down menus could also be provided if desired.Participants are preferably given the option of specifying their entrieseither in terms of financial investment units bought, or dollars to beentered, for each county selected.

Preferably, a whole-state entry can be defined by automatically issuingan equal number of financial investment units for each county in play,within the state in question. This approach would place more money oncounties more likely to be affected, and so would severely down-weightessentially zero-probability counties, such as those in west Texas. Herethe number of financial investment units bought for each county issimply the dollar amount to be entered, divided by the sum of financialinvestment unit prices according to Equation (4), over all counties inthat state.

The sums entered to date in each Hurricane Pool (and available forsubsequent payout) are preferably posted and continuously updated.However, it may be difficult to calculate for potential entrants thepossible payoffs for particular entries that they are contemplating,because those payoffs will depend on the track of the eventual storm inquestion. However, it is also possible to show a minimum payout or“floor” when such feature is desired.

As mentioned above, it is sometimes preferred to provide an expectationof a minimum payout or “floor” for participants that suffer damage froma natural peril event. The “floor” is a minimum payout, conditional onthe county or other geographical area in which an market participantholds an investment unit being “hit.”

XIII. Algorithm Parameters As noted above, several parameters in thefinancial investment unit price algorithm are adjustable. In one examplethese parameters could be defined before the beginning of a given year'sHurricane Pools as follows. These exemplary parameters are:

-   -   K=# of Hurricane Pools that will be opened initially.    -   n=# of counties in the game    -   D=discount rate (as discussed above)    -   F=pricing factor (as discussed above)

The choice for the number, K, of initial Hurricane Pools to be runinvolves a tradeoff between numbers of years when one or more HurricanePools-do not pay off, versus numbers of years when there are more U.S.landfalling hurricanes than initial Hurricane Pools. Using the Poissonprobabilities from FIG. 21 table 1, these tradeoffs are approximately asindicated in FIG. 23, table 3.

If all counties in an included state will be in play, it is necessaryonly to specify the states to be considered in order to determine n. Forexample Oklahoma has a single county with Q≠0, and Kentucky has seven.All eight of these have Q=0.01. Accordingly, it is preferred that thesestates not be included in the financial activity. A large number ofeffectively irrelevant counties may also be excluded under this plan,especially in Texas, but also in Arkansas and Tennessee.

Preferred Characteristics

As noted above, a number of different alternatives and variations inconducting financial activities are possible. The following discussesrepresentative alternatives and variations which are preferred, but notnecessarily required. Although the following exemplary preferredcharacteristics may, generally speaking, be compatible with one another,it is possible that any number of these characteristics could be madeinconsistent with, or mutually exclusive of other characteristics. Theseexemplary characteristics include:

1. Variability factors affecting at least one of said investment priceand said distribution/payout. It is generally preferred that variabilityfactors include, at least a consideration of the time interval betweeninvestment and event occurrence and a defined probability of predictedoutcome, preferably set at the time of investment. Other variabilityfactors may also be incorporated.

2. Prices charged to participants for their chosen investmentspreferably continually change due, for example, to the variabilityfactors at play at a given time. In general, it is preferred that therebe no elimination of price changes to shorten processing delays, or forother reasons.

3. Prices at any given time for any predicted outcome are preferablymade to be the same for all participants.

4. Payouts to successful, qualifying participants are preferably madeaccording to the same set of rules which apply to all participants.Generally speaking, it is preferred that no rewards be given forpreferred participants.

5. All winners (qualifying participants) of the financial activity sharethe pot. That is, it is generally preferred that there are no oddsmultiplying a participant's investment. Also, it is generally preferredthat payouts are not made from the provider's personal account—unlikethe “House” of certain gambling activities which pays out winning betsfrom its own account.

6. Provider does not engage as a participant. For example, it isgenerally preferred it that there be no hedging where, for example,there may be excessive bidding.

7. Participants do not compete against the “house” i.e. the provider.

8. In certain instances, it may be preferable to limit financialactivity to only the United States and its territories and possessions.

9. Financial activity encompasses a single event or type of event over agiven “season”.

10. It is generally preferred that the participants be able toobjectively and independently observe the events for themselves, as theyunfold.

11. It is generally preferred that, apart from financial responsibility,a participant's investment be “accepted” only in terms of data format.Optionally, acceptance can be related to an optional investment cap. Itis generally preferred that there be no extra qualification for eachinvestment occurrence.

12. It is generally preferred that financial activity be carried out asmuch as possible in real-time, and that this be made possible by virtueof rules definitions, especially definitions of events and eventoutcomes which occur in a well defined environment/system. It isgenerally preferred that the selection of events for the financialactivity be limited to an absolute minimum—i.e. a single event.

13. It is generally preferred that the financial activity be restrictedto tropical weather events, and in one instance, only to hurricaneevents.

14. It is generally preferred that the financial activity be furtherrestricted to events comprising at least one of said landfall and saidland track. It may also be preferable in certain instances to limitfinancial activity to hurricanes having a certain category strength atsome defined time during the ongoing financial activity.

15. It is preferable, in certain instances, that multiple stages ofprobability assessment be applied to at least one of said investment andsaid payout.

16. It is preferable in certain instances that the external objectiveindependent information source be limited to the National HurricaneCenter (NHC), and optionally to its subsidiary and/or related agencies(e.g. TPC).

Other Preferences

In addition to the above preferred characteristics, it is generallypreferred that the graphical user interface be used to conveyeducational information to participants, on an ongoing, developingbasis. For example, it is generally preferred that the participants beprovided with a rich source of information to inspire further interestin the financial activity and the skills which it sharpens. For example,it is generally preferred that live feeds of various external objectiveindependent information sources be relayed to the participants on anongoing basis. For example, storm locations and changing intensities,along with their projected path can be displayed on a flat map. Thistype of data can be obtained from the National Hurricane Center, forexample. Other competing predictions from other independent sourcescould also be displayed, preferably in different colors on a common map.

As storms advance and locations change, it is preferred thatcalculations of updated current pricing and returns be displayed on anongoing basis, with any necessary qualifying assumptions being madeavailable to the participants.

Also, it is generally preferred that the current dollars invested forparticular geographical areas be displayed along with historical odds orprobabilities for the geographical area, thus making it possible forparticipants and interested observers to determine what the payout willbe under the specified conditions, if the storm should develop aspredicted. For example, payoffs for a given geographical area canreflect different times of investment, different total amounts of moneyinvested in the overall financial activity, different severity levels orother characteristics of the storm and the probability that the stormwill hit the area of interest, based upon historical data and/or nearterm predictions. It is also generally preferred that the participantsand interested observers be able to access a data window showing thecurrent total of pools invested, and a profile of geographical areaswith the number of investments being made for that local area.

In general, it is preferred that the financial activity have aneducational study component to sharpen a participant's knowledge andskills useful for improving their financial position. This knowledge andskill level will also help the participants cope with the reality ofbeing subjected to potentially harmful storm activity. It is alsogenerally preferred that the financial activity display helpfulinformation to participants, such as checklists of items needed toprepare for an oncoming threatening event. These checklists can helporganize participant's activities in the decreasing preparation timeavailable. If desired, checklist information can be solicited fromparticipants and posted in a public viewing area. In another example, adisplay area can also be provided showing constantly updated damageestimates, threats to life and similar public safety-relatedinformation.

Although exemplary implementations of the invention have been depictedand described in detail herein, it will be apparent to those skilled inthe relevant art that various modifications, additions, substitutions,and the like can be made without departing from the spirit of theinvention and these are therefore considered to be within the scope ofthe invention as defined in the following claims. For example, variouscommunication functions can be grouped into one or more communicationunits to perform one or more communication tasks. Any of the examplesand alternatives provided herein could be combined in whole or in partwith one another, as may be desired, and can be combined with one ormore features set forth herein.

1. A system for conducting a financial activity based on a tropicalweather event, comprising: a financial activity module for facilitatingfinancial activity between a provider and at least two participantsutilizing a graphical user interface, for receiving tropical weatherevent information from an external independent information source ofsuch information and for providing financial activity information to theparticipants utilizing the graphical user interface, includinginformation relating to the tropical weather event information and aplurality of geographic regions in which the financial activity is tooccur and in which a future tropical weather event may occur, theregions presented as a map displayed by the graphical user interface,and at least one communication module for communication between thefinancial activity module and an external independent information sourcefor receiving the tropical weather event information from at least oneexternal independent information source, and for providing indexinformation utilizing the graphical user interface, the indexinformation including an index having an index value varying in responseto one or more tropical weather events, and for presenting to theparticipants at least one derivative product to be traded between theparticipants with respect to a plurality of geographic regions, thederivative product having a value that varies in response to the indexvalue, and settled based on at least one of the tropical weather eventinformation and the index information.
 2. The system according to claim1 wherein the graphical user interface includes an ongoing display ofindex values for each region.
 3. The system according to claim 1 whereinthe graphical user interface includes active elements for each region toaccept input data from a participant.
 4. The method according to claim 1wherein the derivative product comprises one of a futures contract, anoptions contract or an option on futures contract.
 5. The systemaccording to claim 1 wherein the communication module presents a nullregion, available for trading, designating no tropical weather event inany of the plurality of geographic regions.
 6. The system according toclaim 1 further comprising a distribution module for distributing fundsto at least one of the participants, based on settlement of thederivative product.
 7. The system according to claim 1 wherein thefinancial activity module provides index values for each of thegeographic regions.
 8. The system according to claim 1 wherein the atleast one communication module receives index information from aprovider of such information.
 9. A system for conducting a financialactivity based on a tropical weather event, utilizing a graphical userinterface, comprising: a financial activity module for facilitatingfinancial activity between a provider and at least two participantsutilizing a graphical user interface, for receiving tropical weatherevent information from an external independent information source ofsuch information and for providing financial activity information to theparticipants utilizing the graphical user interface, includinginformation relating to the tropical weather event information and aplurality of geographic regions in which the financial activity is tooccur and in which a future tropical weather event may occur, theregions presented as a map displayed by the graphical user interface;the financial activity module providing at least one derivative productto be traded between the participants, for a plurality of geographicregions, the derivative product having a value that varies in responseto the index value, and settled based on at least one of the tropicalweather event information and the index information; the financialactivity module further providing index information including an indexhaving an index value varying in response to one or more tropicalweather events; and at least one communication module for communicationbetween the financial activity module and an external independentinformation source for receiving the tropical weather event informationand for making available to the participants, the tropical weather eventinformation and the index information.
 10. The system according to claim9 wherein the graphical user interface includes an ongoing display ofindex values for each region.
 11. The system according to claim 9wherein the graphical user interface includes active elements for eachregion to accept input data from a participant.
 12. The system accordingto claim 9 wherein the communication module presents a null region,available for trading, designating no tropical weather event in any ofthe plurality of geographic regions.
 13. The system according to claim 9wherein the financial activity module provides index values for each ofthe geographic regions.
 14. The method according to claim 9 wherein thederivative product comprises one of a futures contract, an optionscontract or an option on futures contract.
 15. A system for conducting afinancial activity based on a natural peril event, utilizing a graphicaluser interface, comprising: a financial activity module for facilitatingfinancial activity between a provider and at least two participantsutilizing a graphical user interface, for receiving natural peril eventinformation from an external independent information source of suchinformation and for providing financial activity information to theparticipants utilizing the graphical user interface, includinginformation relating to the natural peril event information and aplurality of geographic regions in which the financial activity is tooccur and in which a future natural peril event may occur, the regionsdisplayed as a map displayed by the graphical user interface; at leastone communication module for communication between the financialactivity module and an external independent information source forreceiving the natural peril event information from at least one externalindependent information source; the financial activity module providingindex information utilizing the graphical user interface, the indexinformation including an index having an index value varying in responseto one or more natural peril events; the financial activity modulepresenting to the participants at least one derivative product to betraded between the participants, for a plurality of geographic regions,the derivative product having a value that varies in response to theindex and which is settled based on at least one of the natural perilevent information and the index information.
 16. The system according toclaim 15 wherein the graphical user interface includes an ongoingdisplay of index values for each region.
 17. The system according toclaim 15 wherein the graphical user interface includes active elementsfor each region to accept input data from a participant.
 18. A method ofconducting a financial activity between a provider and a plurality ofparticipants, based on a tropical weather event, utilizing a graphicaluser interface, comprising: the provider receiving ongoing tropicalweather event information from an external independent informationsource of such information; the provider providing financial activityinformation to the participants, utilizing the graphical user interface,including information relating to the tropical weather event informationand a plurality of geographic regions in which the financial activity isto occur and in which a future tropical weather event may occur, theregions presented as a map displayed by the graphical user interface;the provider offering to the participants, using the graphical userinterface, first prediction data that changes over time, concerning apredicted outcome of the tropical weather event; the provider-receivingthe participants' prediction data of a predicted outcome of the tropicalweather event, using the graphical user interface; the providerreceiving the outcome of the tropical weather event from an externalindependent information source of such information; the provider or athird party comparing the participants' prediction data to the externalinformation to determine if the participant qualifies for successfullypredicting the outcome of the tropical weather event; and making thecomparing determination available to the participants.
 19. The methodaccording to claim 18 wherein the step of presenting to the participantsa plurality of geographic regions for which the financial activity is tooccur includes the step of presenting a null region, available fortrading, designating no tropical weather event in any of the pluralityof geographic regions.
 20. The method according to claim 18 furthercomprising the step of distributing funds to at least one of theparticipants, based at least in part on the comparing determination. 21.The method according to claim 20 further comprising the step ofdistributing a predetermined minimum, amount of funds to participantsqualified to receive funds.
 22. A method of conducting a financialactivity between a provider and a plurality of participants, based on anatural peril event, utilizing a graphical user interface, comprising:the provider receiving ongoing natural peril event information from anexternal independent information source of such information; theprovider providing financial activity information to the participants,utilizing the graphical user interface, including information relatingto the natural peril event information and a plurality of geographicregions in which the financial activity is to occur and in which afuture natural peril event may occur, the regions presented as a mapdisplayed by the graphical user interface; the provider offering to theparticipants, using the graphical user interface, first prediction datathat changes over time, concerning a predicted outcome of the naturalperil event; the provider receiving the participants' prediction data ofa predicted outcome of the natural peril event, using the graphical userinterface; the provider receiving the outcome of the natural peril eventfrom an external independent information source of such information; theprovider or a third party comparing the participants' prediction data tothe external information to determine if the participant qualifies forsuccessfully predicting the outcome of the natural peril event; andmaking the comparing determination available to the participants. 23.The method according to claim 22 wherein the step of presenting to theparticipants a plurality of geographic regions for which the financialactivity is to occur includes the step of presenting a null region,available for trading, designating no natural peril event in any of theplurality of geographic regions.
 24. The method according to claim 22further comprising the step of distributing funds to at least one of theparticipants, based at least in part on the comparing determination. 25.The method according to claim 24 further comprising the step ofdistributing a predetermined minimum, amount of funds to participantsqualified to receive funds.